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Sunday, June 9, 2024

Burden of proof (law)

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Burden_of_proof_(law)

In a legal dispute, one party has the burden of proof to show that they are correct, while the other party has no such burden and is presumed to be correct. The burden of proof requires a party to produce evidence to establish the truth of facts needed to satisfy all the required legal elements of the dispute.

The burden of proof is usually on the person who brings a claim in a dispute. It is often associated with the Latin maxim semper necessitas probandi incumbit ei qui agit, a translation of which is: "the necessity of proof always lies with the person who lays charges." In civil suits, for example, the plaintiff bears the burden of proof that the defendant's action or inaction caused injury to the plaintiff, and the defendant bears the burden of proving an affirmative defense. The burden of proof is on the prosecutor for criminal cases, and the defendant is presumed innocent. If the claimant fails to discharge the burden of proof to prove their case, the claim will be dismissed.

Definition

A "burden of proof" is a party's duty to prove a disputed assertion or charge, and includes the burden of production (providing enough evidence on an issue so that the trier-of-fact decides it rather than in a peremptory ruling like a directed verdict) and the burden of persuasion (standard of proof such as preponderance of the evidence).

A "burden of persuasion" or "risk of non-persuasion" is an obligation that remains on a single party for the duration of the court proceeding. Once the burden has been entirely discharged to the satisfaction of the trier of fact, the party carrying the burden will succeed in its claim. For example, the presumption of innocence in a criminal case places a legal burden upon the prosecution to prove all elements of the offense (generally beyond a reasonable doubt), and to disprove all the defenses except for affirmative defenses in which the proof of non-existence of all affirmative defense(s) is not constitutionally required of the prosecution.

The burden of persuasion should not be confused with the evidential burden, or burden of production, or duty of producing (or going forward with evidence) which is an obligation that may shift between parties over the course of the hearing or trial. The evidential burden is the burden to adduce sufficient evidence to properly raise an issue at court.

There is no burden of proof with regard to motive or animus in criminal cases in the United States. The intent surrounding an offense is nevertheless crucial to the elements of the offense in a first-degree-murder conviction. This brings up the ethical dilemma of whether or not a death sentence should be imposed when the defendant's motives or intentions are the contingent factors in sentencing. However, in some cases such as defamation suits with a public figure as the defamed party, the public figure must prove actual malice.

Standard of proof in the United States

Burden of proof refers most generally to the obligation of a party to prove its allegations at trial. In a civil case, the plaintiff sets forth its allegations in a complaint, petition or other pleading. The defendant is then required to file a responsive pleading denying some or all of the allegations and setting forth any affirmative facts in defense. Each party has the burden of proof of its allegations.

Legal standards for burden of proof

Some evidence

Per Superintendent v. Hill (1985), in order to take away a prisoner's good conduct time for a disciplinary violation, prison officials need only have "some evidence", i.e., "a modicum of evidence"; however, the sentencing judge is under no obligation to adhere to good/work time constraints, nor are they required to credit time served.

Reasonable indications

"Reasonable indication (also known as reasonable suspicion) is substantially lower than probable cause; factors to consider are those facts and circumstances a prudent investigator would consider, but must include facts or circumstances indicating a past, current, or impending violation; an objective factual basis must be present, a mere 'hunch' is insufficient."

The reasonable indication standard is used in interpreting trade law in determining if the United States has been materially injured.

Reasonable suspicion

Reasonable suspicion is a low standard of proof to determine whether a brief investigative stop or search by a police officer or any government agent is warranted. This stop or search must be brief; its thoroughness is proportional to, and limited by, the low standard of evidence. A more definite standard of proof (often probable cause) would be required to justify a more thorough stop/search. In Terry v. Ohio, 392 U.S. 1 (1968), the Supreme Court ruled that reasonable suspicion requires specific, articulable, and individualized suspicion that crime is afoot. A mere guess or "hunch" is not enough to constitute reasonable suspicion.

An investigatory stop is a seizure under the Fourth Amendment. The state must justify the seizure by showing that the officer conducting the stop had a reasonable articulable suspicion that criminal activity was afoot. The important point is that officers cannot deprive a citizen of liberty unless the officer can point to specific facts and circumstances and inferences therefrom that would amount to a reasonable suspicion. The officer must be prepared to establish that criminal activity was a logical explanation for what they perceived. The requirement serves to prevent officers from stopping individuals based merely on hunches or unfounded suspicions. The purpose of the stop and detention is to investigate to the extent necessary to confirm or dispel the original suspicion. If the initial confrontation with the person stopped dispels suspicion of criminal activity the officer must end the detention and allow the person to go about their business. If the investigation confirms the officer's initial suspicion or reveals evidence that would justify continued detention the officer may require the person detained to remain at the scene until further investigation is complete, and may give rise to the level of probable cause.

Reasonable to believe

In Arizona v. Gant (2009), the United States Supreme Court defined a new standard, that of "reasonable to believe". This standard applies only to vehicle searches after the suspect has been placed under arrest. The Court overruled New York v. Belton (1981) and concluded that police officers are allowed to go back and search a vehicle incident to a suspect's arrest only where it is "reasonable to believe" that there is more evidence in the vehicle of the crime for which the suspect was arrested.

There is still an ongoing debate as to the exact meaning of this phrase. Some courts have said it should be a new standard while others have equated it with the "reasonable suspicion" of the Terry stop. Most courts have agreed it is somewhere less than probable cause.

Probable cause

Probable cause is a higher standard of proof than reasonable suspicion, which is used in the United States to determine whether a search, or an arrest, is unreasonable. It is also used by grand juries to determine whether to issue an indictment. In the civil context, this standard is often used where plaintiffs are seeking a prejudgement remedy.

In the criminal context, the U.S. Supreme Court in United States v. Sokolow, 490 U.S. 1 (1989), determined that probable cause requires "a fair probability that contraband or evidence of a crime will be found". The primary issue was whether Drug Enforcement Administration agents had a reason to execute a search. Courts have traditionally interpreted the idea of "a fair probability" as meaning whether a fair-minded evaluator would have reason to find it more likely than not that a fact (or ultimate fact) is true, which is quantified as a 51% certainty standard (using whole numbers as the increment of measurement). Some courts and scholars have suggested probable cause could, in some circumstances, allow for a fact to be established as true to a standard of less than 51%, but as of August 2019, the United States Supreme Court has never ruled that the quantification of probable cause is anything less than 51%. Probable cause can be contrasted with "reasonable articulable suspicion" which requires a police officer to have an unquantified amount of certainty the courts say is well below 51% before briefly detaining a suspect (without consent) to pat them down and attempt to question them. The "beyond reasonable doubt" standard, used by criminal juries in the United States to determine guilt for a crime, also contrasts with probable cause which courts hold requires an unquantified level of proof well above that of probable cause's 51%. Though it is beyond the scope of this topic, when courts review whether 51% probable cause certainty was a reasonable judgment, the legal inquiry is different for police officers in the field than it would be for grand jurors. In Franks v. Delaware, the U.S. Supreme Court held that probable cause requires that there not be "reckless disregard for the truth" of the facts asserted.

Examples of a police officer's truth-certainty standards in the field and their practical consequences are offered below:

  • no level of evidence required: a knowing and voluntary consent-based encounter between police officer and another person
  • reasonable articulable suspicion of criminal activity required: an involuntary stop initiated by the officer to briefly detain, attempt to question, and pat down outer clothing of a person of interest to police.
  • probable cause of 51% truth or higher required that a crime was committed by a specific person: arrest and/or grand jury indictment of that person.

Some credible evidence

Some credible evidence is one of the least demanding standards of proof. This proof standard is often used in administrative law settings and in some states to initiate Child Protective Services (CPS) proceedings. This proof standard is used where short-term intervention is needed urgently, such as when a child is arguably in immediate danger from a parent or guardian. The "some credible evidence" standard is used as a legal placeholder to bring some controversy before a trier of fact, and into a legal process. It is on the order of the factual standard of proof needed to achieve a finding of "probable cause" used in ex parte threshold determinations needed before a court will issue a search warrant. It is a lower standard of proof than the "preponderance of the evidence" standard. The standard does not require the fact-finder to weigh conflicting evidence, and merely requires the investigator or prosecutor to present the bare minimum of material credible evidence to support the allegations against the subject, or in support of the allegation; see Valmonte v. Bane, 18 F.3d 992 (2nd Cir. 1994). In some Federal Appellate Circuit Courts, such as the Second Circuit, the "some credible evidence" standard has been found constitutionally insufficient to protect liberty interests of the parties in controversy at CPS hearings.

Preponderance of the evidence

Preponderance of the evidence (American English), also known as balance of probabilities (British English), is the standard required in civil cases, including family court determinations solely involving money, such as child support under the Child Support Standards Act, and in child custody determinations between parties having equal legal rights respecting a child. It is also the standard of proof by which the defendant must prove affirmative defenses or mitigating circumstances in civil or criminal court in the United States. In civil courts, aggravating circumstances also only have to be proven by a preponderance of the evidence, as opposed to beyond reasonable doubt (as in criminal court).

The standard is met if the proposition is more likely to be true than not true. Lord Denning, in Miller v. Minister of Pensions, described it simply as "more probable than not". Another high-level way of interpreting that is that the plaintiff’s case (evidence) be 51% likely. A more precise statement is that “the weight [of the evidence, including in calculating such a percentage] is determined not by the amount of evidence, but by its quality.” The author goes on to affirm that preponderance is “merely enough to tip the scales” towards one party; however, that tilt need only be so slight as the weight of a “feather.” Until 1970, it was also the standard used in juvenile court in the United States. Compared to the criminal standard of “proof beyond a reasonable doubt,” the preponderance of the evidence standard is “a somewhat easier standard to meet.”

Preponderance of the evidence is also the standard of proof used in United States administrative law. In at least one case, there is a statutory definition of the standard.

While there is no federal definition, such as by definition of the courts or by statute applicable to all cases, The Merit Systems Protection Board’s has codified their definition at 5 CFR 1201.56(c)(2). MSPB defines the standard as “The degree of relevant evidence that a reasonable person, considering the record as a whole, would accept as sufficient to find that a contested fact is more likely to be true than untrue.” One author highlights the phrase “more likely to be true than untrue” as the critical component of the definition.

From 2013 to 2020, the Department of Education required schools to use a preponderance of evidence standard in evaluating sexual assault claims (USA).

Clear and convincing evidence

Clear and convincing evidence is a higher level of burden of persuasion than "preponderance of the evidence", but less than "beyond reasonable doubt". It is employed intra-adjudicatively in administrative court determinations, as well as in civil and certain criminal procedure in the United States. For example, a prisoner seeking habeas corpus relief from capital punishment must prove his factual innocence by clear and convincing evidence. New York State uses this standard when a court must determine whether to involuntarily hospitalize a mentally ill patient or to issue an Assisted Outpatient Treatment Order. This standard was also codified by the United States Supreme Court in all mental health civil commitment cases.

This standard is used in many types of equity cases, including paternity, persons in need of supervision, child custody, the probate of both wills and living wills, petitions to remove a person from life support ("right to die" cases), mental hygiene and involuntary hospitalizations, and many similar cases.

Clear and convincing evidence is the standard of proof used for immunity from prosecution under Florida's stand-your-ground law. Once raised by the defense, the state must present its evidence in a pre-trial hearing, showing that the statutory prerequisites have not been met, and then request that the court deny a motion for declaration of immunity. The judge must then decide from clear and convincing evidence whether to grant immunity. This is a lower burden than "beyond a reasonable doubt", the threshold a prosecutor must meet at any proceeding criminal trial, but higher than the "probable cause" threshold generally required for indictment.

Clear and convincing proof means that the evidence presented by a party during the trial must be highly and substantially more probable to be true than not and the trier of fact must have a firm belief or conviction in its factuality. In this standard, a greater degree of believability must be met than the common standard of proof in civil actions (i.e. preponderance of the evidence), which only requires that the facts as a threshold be more likely than not to prove the issue for which they are asserted.

This standard is also known as "clear, convincing, and satisfactory evidence"; "clear, cognizant, and convincing evidence", and is applied in cases or situations involving an equitable remedy or where a presumptive civil liberty interest exists. For example, this is the standard or quantum of evidence use to probate a last will and testament.

Beyond reasonable doubt

This is the highest standard used as the burden of proof in Anglo-American jurisprudence and typically only applies in juvenile delinquency proceedings, criminal proceedings, and when considering aggravating circumstances in criminal proceedings. It has been described, in negative terms, as a proof having been met if there is no plausible reason to believe otherwise. If there is a real doubt, based upon reason and common sense after careful and impartial consideration of all the evidence, or lack of evidence, in a case, then the level of proof has not been met.

Proof beyond a reasonable doubt, therefore, is proof of such a convincing character that one would be willing to rely and act upon it without hesitation in the most important of one's own affairs. However, it does not mean an absolute certainty. The standard that must be met by the prosecution's evidence in a criminal prosecution is that no other logical explanation can be derived from the facts except that the defendant committed the crime, thereby overcoming the presumption that a person is innocent unless and until proven guilty.

If the trier of fact has no doubt as to the defendant's guilt, or if their only doubts are unreasonable doubts, then the prosecutor has proved the defendant's guilt beyond a reasonable doubt and the defendant should be pronounced guilty.

The term connotes that evidence establishes a particular point to a moral certainty which precludes the existence of any reasonable alternatives. It does not mean that no doubt exists as to the accused's guilt, but only that no reasonable doubt is possible from the evidence presented. Further to this notion of moral certainty, where the trier of fact relies on proof that is solely circumstantial, i.e., when conviction is based entirely on circumstantial evidence, certain jurisdictions specifically require the prosecution's burden of proof to be such that the facts proved must exclude to a moral certainty every reasonable hypothesis or inference other than guilt.

The main reason that this high level of proof is demanded in criminal trials is that such proceedings can result in the deprivation of a defendant's liberty or even in their death. These outcomes are far more severe than in civil trials, in which monetary damages are the common remedy.

Another noncriminal instance in which proof beyond a reasonable doubt is applied is LPS conservatorship.

Standard of proof in the United Kingdom

In the three jurisdictions of the UK (Northern Ireland; England and Wales; and Scotland) there are only two standards of proof in trials. There are others which are defined in statutes, such as those relating to police powers.

The criminal standard was formerly described as "beyond reasonable doubt". That standard remains, and the words commonly used, though the Judicial Studies Board guidance is that juries might be assisted by being told that to convict they must be persuaded "so that you are sure".

The civil standard is 'the balance of probabilities', often referred to in judgments as "more likely than not".

The civil standard is also used in criminal trials in relation to those defenses which must be proven by the defendant (for example, the statutory defense to drunk in charge that there was no likelihood of the accused driving while still over the alcohol limit). However, where the law does not stipulate a reverse burden of proof, the defendant need only raise the issue and it is then for the prosecution to negate the defence to the criminal standard in the usual way (for example, that of self-defence).

Prior to the decision of the House of Lords in Re B (A Child) [2008] UKHL 35 there had been some confusion – even at the Court of Appeal – as to whether there was some intermediate standard, described as the 'heightened standard'. The House of Lords found that there was not. As the above description of the American system shows, anxiety by judges about making decisions on very serious matters on the basis of the balance of probabilities had led to a departure from the common law principles of just two standards. Baroness Hale said:

70. ... Neither the seriousness of the allegation nor the seriousness of the consequences should make any difference to the standard of proof to be applied in determining the facts. The inherent probabilities are simply something to be taken into account, where relevant, in deciding where the truth lies.

72. ... there is no logical or necessary connection between seriousness and probability. Some seriously harmful behaviour, such as murder, is sufficiently rare to be inherently improbable in most circumstances. Even then there are circumstances, such as a body with its throat cut and no weapon to hand, where it is not at all improbable. Other seriously harmful behaviour, such as alcohol or drug abuse, is regrettably all too common and not at all improbable. Nor are serious allegations made in a vacuum. Consider the famous example of the animal seen in Regent’s Park. If it is seen outside the zoo on a stretch of greensward regularly used for walking dogs, then of course it is more likely to be a dog than a lion. If it is seen in the zoo next to the lions’ enclosure when the door is open, then it may well be more likely to be a lion than a dog.

The task for the tribunal then when faced with serious allegations is to recognize that their seriousness generally means they are inherently unlikely, such that to be satisfied that a fact is more likely than not the evidence must be of a good quality. But the standard of proof remains 'the balance of probabilities'.

Standard of proof in Australia

In Australia two standards of proof are applied at common law: the criminal standard and the civil standard. It is possible for other standards of proof to be applied where required by law.

Criminal standard

The criminal standard in Australia is, 'beyond reasonable doubt'. An offence against a Commonwealth law, with a term of imprisonment in excess of 12 months is an 'indictable offence'; and is constitutionally required to be tried before jury of 12 people. Offences that do not carry a term of imprisonment exceeding 12 months are called 'Summary Offences'. Some offences (with a term of imprisonment <10 years) may be heard by a court of summary jurisdiction, a.k.a. Magistrates Court with the consent of all parties; however the court may not impose a sentence greater than 12 months. Juries are required to make findings of guilt 'beyond reasonable doubt' for criminal matters.

The Australian constitution does not expressly provide that criminal trials must be 'fair', nor does it set out the elements of a fair trial, but it may by implication protect other attributes. The High Court has moved toward, but not yet, entrenched procedural fairness as a constitutional right. If it did so, this would have the potential to constitutionalise the 'beyond reasonable doubt' standard in criminal proceedings.

State offences are not subject to the constitution's section 80 requirement for a jury. However, the case of Kirk constrains the way that State courts may operate during criminal trials per the Kable Doctrine.

Civil standard

In Australia, the civil standard is termed the 'balance of probabilities'. In Australia, the 'balance of probabilities' involves considerations that the evidence required to establish a fact at the civil standard will vary with the seriousness of what is being alleged. Although it has been noted a similar approach is taken in Canada. In the United Kingdom the evidential requirements of the civil standard of proof don't vary with the seriousness of an allegation.

The case law that establishes this is Briginshaw v Briginshaw, which is the fifth most cited decision of Australia's High Court. The case has since been incorporated into the uniform evidence law. The Briginshaw principle was articulated by Dixon in that case in these terms:

...it is enough that the affirmative of an allegation is made out to the reasonable satisfaction of the tribunal. But reasonable satisfaction is not a state of mind that is attained or established independently of the nature and consequence of the fact or facts to be proved. The seriousness of an allegation made, the inherent unlikelihood of an occurrence of a given description, or the gravity of the consequences flowing from a particular finding are considerations which must affect the answer to the question whether the issue has been proved to the reasonable satisfaction of the tribunal. In such matters “reasonable satisfaction” should not be produced by inexact proofs, indefinite testimony, or indirect inferences. Everyone must feel that, when, for instance, the issue is on which of two dates an admitted occurrence took place, a satisfactory conclusion may be reached on materials of a kind that would not satisfy any sound and prudent judgment if the question was whether some act had been done involving grave moral delinquency

The Briginshaw principle is sometimes incorrectly referred to as the Briginshaw standard of proof, in Qantas Airways Limited v. Gama Justices French and Jacobson stated the "Briginshaw test does not create any third standard of proof between the civil and the criminal."

In the High Court case of G v. H Justices Deane, Dawson and Gaudron stated "Not every case involves issues of importance and gravity in the Briginshaw v. Briginshaw sense. The need to proceed with caution is clear if, for example, there is an allegation of fraud or an allegation of criminal or moral wrongdoing..".

An example of the Briginshaw principle applied in practice is the case of Ben Roberts-Smith where, due to the gravity of the allegations, Fairfax Media was required to rely on stronger proof than in the context of a normal allegation to win their case. In the end, despite the high burden of proof required, Fairfax won the trial, with Besanko ruling that it was proven he "broke the moral and legal rules of military engagement and is therefore a criminal".

Melbourne Law School professor Jeremy Gans, has noted that for particularly serious allegations, such as sexual assault, "It's hard to see how the Briginshaw principle is much different to beyond reasonable doubt". The decision has also been noted for affecting the ability of litigants to seek redress in anti-discrimination lawsuits, due to the seriousness of such allegations.

Other standards for presenting cases or defenses

Air of reality

The "air of reality" is a standard of proof used in Canada to determine whether a criminal defense may be used. The test asks whether a defense can be successful if it is assumed that all the claimed facts are to be true. In most cases, the burden of proof rests solely on the prosecution, negating the need for a defense of this kind. However, when exceptions arise and the burden of proof has been shifted to the defendant, they are required to establish a defense that bears an "air of reality". Two instances in which such a case might arise are, first, when a prima facie case has been made against the defendant or, second, when the defense mounts an affirmative defense, such as the insanity defense. This is similar to the concept of Summary judgment in the United States, though not identical.

Evidentiary standards of proof

Depending on the legal venue or intra-case hearing, varying levels of reliability of proof are considered dispositive of the inquiry being entertained. If the subject threshold level of reliability has been met by the presentation of the evidence, then the thing is considered legally proved for that trial, hearing or inquest. For example, in California, several evidentiary presumptions are codified, including a presumption that the owner of legal title is the beneficial owner (rebuttable only by clear and convincing evidence).

Examples

Criminal law

Criminal cases usually place the burden of proof on the prosecutor (expressed in the Latin brocard ei incumbit probatio qui dicit, non qui negat, "the burden of proof rests on who asserts, not on who denies"). This principle is known as the presumption of innocence, and is summed up with "innocent until proven guilty", but is not upheld in all legal systems or jurisdictions. Where it is upheld, the accused will be found not guilty if this burden of proof is not sufficiently shown by the prosecution. The presumption of innocence means three things:

  • With respect to the critical facts of a case the defendant has no burden of proof whatsoever.
  • The state must prove the critical facts of the case to the appropriate level of certainty.
  • The jury is not to draw any inferences adverse to the defendant from the fact that they have been charged with a crime and are present in court facing the charges against them.

For example, if the defendant (D) is charged with murder, the prosecutor (P) bears the burden of proof to show the jury that D did indeed murder someone.

  • Burden of proof: P
    • Burden of production: P has to show some evidence that D had committed murder. The United States Supreme Court has ruled that the Constitution requires enough evidence to justify a rational trier of fact to find guilt beyond a reasonable doubt. If the judge rules that such burden has been met, then it is up to the jury itself to decide if they are, in fact, convinced of guilty beyond a reasonable doubt. If the judge finds there is not enough evidence under the standard, the case must be dismissed (or a subsequent guilty verdict must be vacated and the charges dismissed).
      • e.g. witness, forensic evidence, autopsy report
      • Failure to meet the burden: the issue will be decided as a matter of law. In this case, D is presumed innocent
    • Burden of persuasion: if at the close of evidence, the jury cannot decide if P has established with relevant level of certainty that D had committed murder, the jury must find D not guilty of the crime of murder
      • Measure of proof: P has to prove every element of the offense beyond a reasonable doubt, but not necessarily prove every single fact beyond a reasonable doubt.

However, in England and Wales, the Magistrates' Courts Act 1980, s.101 stipulates that where a defendant relies on some "exception, exemption, proviso, excuse or qualification" in their defence in a summary trial, the legal burden of proof as to that exception falls on the defendant, though only on the balance of probabilities. For example, a person charged with being drunk in charge of a motor vehicle can raise the defense that there was no likelihood of their driving while drunk. The prosecution has the legal burden of proof beyond reasonable doubt that the defendant exceeded the legal limit of alcohol and was in control of a motor vehicle. Possession of the keys is usually sufficient to prove control, even if the defendant is not in the vehicle and is perhaps in a nearby bar. That being proved, the defendant has the legal burden of proof on the balance of probabilities that they were not likely to drive.

In 2002, such practice in England and Wales was challenged as contrary to the European Convention on Human Rights (ECHR), art.6(2) guaranteeing right to a fair trial. The House of Lords held that:

  • A mere evidential burden did not contravene art. 6(2);
  • A legal / persuasive burden did not necessarily contravene art. 6(2) so long as confined within reasonable limits, considering the questions:
    • What must the prosecution prove to transfer burden to the defendant?
    • Is the defendant required to prove something difficult or easily within his access?
    • What threat to society is the provision designed to combat?

In some cases, there is a reverse onus on the accused. A typical example is that of a hit-and-run charge prosecuted under the Canadian Criminal Code. The defendant is presumed to have fled the scene of a crash, to avoid civil or criminal liability, if the prosecution can prove the remaining essential elements of the offense.

Civil law

In civil law cases, such as a dispute over a contract or a claim about an accidental injury, the burden of proof usually requires the plaintiff to convince the trier of fact (whether judge or jury) of the plaintiff's entitlement to the relief sought. This means that the plaintiff must prove each element of the claim, or cause of action, in order to recover.

This rule is not absolute in civil lawsuits; unlike with criminal offenses, laws may establish a different burden of proof, or the burden in an individual case may be reversed as a matter of fairness. For example, if a bank or government agency has a legal duty to keep certain records, and a lawsuit alleges that the proper records were not kept, then the plaintiff may not be required to prove a negative; instead, the respondent could be required to prove to the court that the records were kept.

Civil cases of the U.S. Supreme Court

In Keyes v. Sch. Dist. No. 1, the United States Supreme Court stated: "There are no hard-and-fast standards governing the allocation of the burden of proof in every situation. The issue, rather, 'is merely a question of policy and fairness based on experience in the different situations'." For support, the Court cited 9 John H. Wigmore, Evidence § 2486, at 275 (3d ed. 1940). In Keyes, the Supreme Court held that if "school authorities have been found to have practiced purposeful segregation in part of a school system", the burden of persuasion shifts to the school to prove that it did not engage in such discrimination in other segregated schools in the same system.

In Director, Office of Workers' Compensation Programs v. Greenwich Collieries, the Supreme Court explained that "burden of proof" is ambiguous because it has historically referred to two distinct burdens: the burden of persuasion, and the burden of production.

The Supreme Court discussed how courts should allocate the burden of proof (i.e., the burden of persuasion) in Schaffer ex rel. Schaffer v. Weast. The Supreme Court explained that if a statute is silent about the burden of persuasion, the court will "begin with the ordinary default rule that plaintiffs bear the risk of failing to prove their claims". In support of this proposition, the Court cited 2 J. Strong, McCormick on Evidence § 337, 412 (5th ed. 1999), which states:

The burdens of pleading and proof with regard to most facts have been and should be assigned to the plaintiff who generally seeks to change the present state of affairs and who therefore naturally should be expected to bear the risk of failure of proof or persuasion.

At the same time, the Supreme Court also recognized "The ordinary default rule, of course, admits of exceptions. ... For example, the burden of persuasion as to certain elements of a plaintiff's claim may be shifted to defendants, when such elements can fairly be characterized as affirmative defenses or exemptions. ... Under some circumstances this Court has even placed the burden of persuasion over an entire claim on the defendant. ... [Nonetheless,] [a]bsent some reason to believe that Congress intended otherwise, therefore, [the Supreme Court] will conclude that the burden of persuasion lies where it usually falls, upon the party seeking relief."

Bootstrapping

From Wikipedia, the free encyclopedia

In general, bootstrapping usually refers to a self-starting process that is supposed to continue or grow without external input.

Etymology

A pair of boots with one bootstrap visible

Tall boots may have a tab, loop or handle at the top known as a bootstrap, allowing one to use fingers or a boot hook tool to help pull the boots on. The saying "to pull oneself up by one's bootstraps" was already in use during the 19th century as an example of an impossible task. The idiom dates at least to 1834, when it appeared in the Workingman's Advocate: "It is conjectured that Mr. Murphee will now be enabled to hand himself over the Cumberland river or a barn yard fence by the straps of his boots." In 1860 it appeared in a comment on philosophy of mind: "The attempt of the mind to analyze itself  an effort analogous to one who would lift himself by his own bootstraps." Bootstrap as a metaphor, meaning to better oneself by one's own unaided efforts, was in use in 1922. This metaphor spawned additional metaphors for a series of self-sustaining processes that proceed without external help.

Baron Munchausen pulls himself and his horse out of a swamp by his pigtail.

The term is sometimes attributed to a story in Rudolf Erich Raspe's The Surprising Adventures of Baron Munchausen, but in that story Baron Munchausen pulls himself (and his horse) out of a swamp by his hair (specifically, his pigtail), not by his bootstraps – and no explicit reference to bootstraps has been found elsewhere in the various versions of the Munchausen tales.

Originally meant to attempt something ludicrously far-fetched or even impossible, the phrase "Pull yourself up by your bootstraps!" has since been utilized as a narrative for economic mobility or a cure for depression. That idea is believed to have been popularized by American writer Horatio Alger in the 19th century. To request that someone "bootstrap" is to suggest that they might overcome great difficulty by sheer force of will.

Critics have observed that the phrase is used to portray unfair situations as far more meritocratic than they really are. A 2009 study found that 77% of Americans believe that wealth is often the result of hard work. Various studies have found that the main predictor of future wealth is not IQ or hard work, but initial wealth.

Applications

Computing

In computer technology, the term bootstrapping refers to language compilers that are able to be coded in the same language. (For example, a C compiler is now written in the C language. Once the basic compiler is written, improvements can be iteratively made, thus pulling the language up by its bootstraps). Also, booting usually refers to the process of loading the basic software into the memory of a computer after power-on or general reset, the kernel will load the operating system which will then take care of loading other device drivers and software as needed.

Software loading and execution

Booting is the process of starting a computer, specifically with regard to starting its software. The process involves a chain of stages, in which at each stage, a relatively small and simple program loads and then executes the larger, more complicated program of the next stage. It is in this sense that the computer "pulls itself up by its bootstraps"; i.e., it improves itself by its own efforts. Booting is a chain of events that starts with execution of hardware-based procedures and may then hand-off to firmware and software which is loaded into main memory. Booting often involves processes such as performing self-tests, loading configuration settings, loading a BIOS, resident monitors, a hypervisor, an operating system, or utility software.

The computer term bootstrap began as a metaphor in the 1950s. In computers, pressing a bootstrap button caused a hardwired program to read a bootstrap program from an input unit. The computer would then execute the bootstrap program, which caused it to read more program instructions. It became a self-sustaining process that proceeded without external help from manually entered instructions. As a computing term, bootstrap has been used since at least 1953.

Software development

Bootstrapping can also refer to the development of successively more complex, faster programming environments. The simplest environment will be, perhaps, a very basic text editor (e.g., ed) and an assembler program. Using these tools, one can write a more complex text editor, and a simple compiler for a higher-level language and so on, until one can have a graphical IDE and an extremely high-level programming language.

Historically, bootstrapping also refers to an early technique for computer program development on new hardware. The technique described in this paragraph has been replaced by the use of a cross compiler executed by a pre-existing computer. Bootstrapping in program development began during the 1950s when each program was constructed on paper in decimal code or in binary code, bit by bit (1s and 0s), because there was no high-level computer language, no compiler, no assembler, and no linker. A tiny assembler program was hand-coded for a new computer (for example the IBM 650) which converted a few instructions into binary or decimal code: A1. This simple assembler program was then rewritten in its just-defined assembly language but with extensions that would enable the use of some additional mnemonics for more complex operation codes. The enhanced assembler's source program was then assembled by its predecessor's executable (A1) into binary or decimal code to give A2, and the cycle repeated (now with those enhancements available), until the entire instruction set was coded, branch addresses were automatically calculated, and other conveniences (such as conditional assembly, macros, optimisations, etc.) established. This was how the early Symbolic Optimal Assembly Program (SOAP) was developed. Compilers, linkers, loaders, and utilities were then coded in assembly language, further continuing the bootstrapping process of developing complex software systems by using simpler software.

The term was also championed by Doug Engelbart to refer to his belief that organizations could better evolve by improving the process they use for improvement (thus obtaining a compounding effect over time). His SRI team that developed the NLS hypertext system applied this strategy by using the tool they had developed to improve the tool.

Compilers

The development of compilers for new programming languages first developed in an existing language but then rewritten in the new language and compiled by itself, is another example of the bootstrapping notion.

Installers

During the installation of computer programs, it is sometimes necessary to update the installer or package manager itself. The common pattern for this is to use a small executable bootstrapper file (e.g., setup.exe) which updates the installer and starts the real installation after the update. Sometimes the bootstrapper also installs other prerequisites for the software during the bootstrapping process.

Overlay networks

A bootstrapping node, also known as a rendezvous host, is a node in an overlay network that provides initial configuration information to newly joining nodes so that they may successfully join the overlay network.

Discrete-event simulation

A type of computer simulation called discrete-event simulation represents the operation of a system as a chronological sequence of events. A technique called bootstrapping the simulation model is used, which bootstraps initial data points using a pseudorandom number generator to schedule an initial set of pending events, which schedule additional events, and with time, the distribution of event times approaches its steady state—the bootstrapping behavior is overwhelmed by steady-state behavior.

Artificial intelligence and machine learning

Bootstrapping is a technique used to iteratively improve a classifier's performance. Typically, multiple classifiers will be trained on different sets of the input data, and on prediction tasks the output of the different classifiers will be combined.

Seed AI is a hypothesized type of artificial intelligence capable of recursive self-improvement. Having improved itself, it would become better at improving itself, potentially leading to an exponential increase in intelligence. No such AI is known to exist, but it remains an active field of research. Seed AI is a significant part of some theories about the technological singularity: proponents believe that the development of seed AI will rapidly yield ever-smarter intelligence (via bootstrapping) and thus a new era.

Statistics

Bootstrapping is a resampling technique used to obtain estimates of summary statistics.

Business

Bootstrapping in business means starting a business without external help or working capital. Entrepreneurs in the startup development phase of their company survive through internal cash flow and are very cautious with their expenses. Generally at the start of a venture, a small amount of money will be set aside for the bootstrap process. Bootstrapping can also be a supplement for econometric models. Bootstrapping was also expanded upon in the book Bootstrap Business by Richard Christiansen, the Harvard Business Review article The Art of Bootstrapping and the follow-up book The Origin and Evolution of New Businesses by Amar Bhide. There is also an entire bible written on how to properly bootstrap by Seth Godin.

Experts have noted that several common stages exist for bootstrapping a business venture:

  1. Birth-stage: This is the first stage to bootstrapping by which the entrepreneur utilizes any personal savings or borrowed and/or invested money from friends and family to launch the business. It is also possible for the business owner to be running or working for another organization at the time which may help to fuel their business and cover initial expenses.
  2. Funding from sales to consumers-stage: In this particular stage, money from customers is used to keep the business operating afloat. Once expenses caused by normal day-to-day business operations are met, the rate growth usually increases.
  3. Outsourcing-stage: At this point in the company's existence, the entrepreneur in question normally concentrates on the specific operating activities. This is the time in which entrepreneurs decide how to improve and upgrade equipment (subsequently increasing output) or even employing new staff members. At this point in time, the company may seek loans or even lean on other methods of additional funding such as venture capital to help with expansion and other improvements.

There are many types of companies that are eligible for bootstrapping. Early-stage companies that do not necessarily require large influxes of capital (particularly from outside sources) qualify. This would specifically allow for flexibility for the business and time to grow. Serial entrepreneur companies could also possibly reap the benefits of bootstrapping. These are organizations whereby the founder has money from the sale of a previous companies they can use to invest.

There are different methods of bootstrapping. Future business owners aspiring to use bootstrapping as way of launching their product or service often use the following methods:

  • Using accessible money from their own personal savings.
  • Managing their working capital in a way that minimizes their company's accounts receivable.
  • Cashing out 401k retirement funds and pay them off at later dates.
  • Gradually increasing the business’ accounts payable through delaying payments or even renting equipment instead of buying them.

Bootstrapping is often considered successful. When taking into account statistics provided by Fundera, approximately 77% of small business rely on some sort of personal investment and or savings in order to fund their startup ventures. The average small business venture requires approximately $10,000 in startup capital with a third of small business launching with less than $5,000 bootstrapped.

Based on startup data presented by Entrepreneur.com, in comparison other methods of funding, bootstrapping is more commonly used than others. “0.91% of startups are funded by angel investors, while 0.05% are funded by VCs. In contrast, 57 percent of startups are funded by personal loans and credit, while 38 percent receive funding from family and friends.”

Some examples of successful entrepreneurs that have used bootstrapping in order to finance their businesses include serial entrepreneur Mark Cuban. He has publicly endorsed bootstrapping claiming that “If you can start on your own … do it by [yourself] without having to go out and raise money.” When asked why he believed this approach was most necessary, he replied, “I think the biggest mistake people make is once they have an idea and the goal of starting a business, they think they have to raise money. And once you raise money, that’s not an accomplishment, that’s an obligation” because “now, you’re reporting to whoever you raised money from.”

Bootstrapped companies such as Apple Inc. (APPL), eBay Inc. (EBAY) and Coca-Cola Co. have also claimed that they attribute some of their success to the fact that this method of funding enables them to remain highly focused on a specific array of profitable product.

Startups can grow by reinvesting profits in its own growth if bootstrapping costs are low and return on investment is high. This financing approach allows owners to maintain control of their business and forces them to spend with discipline. In addition, bootstrapping allows startups to focus on customers rather than investors, thereby increasing the likelihood of creating a profitable business. This leaves startups with a better exit strategy with greater returns.

Leveraged buyouts, or highly leveraged or "bootstrap" transactions, occur when an investor acquires a controlling interest in a company's equity and where a significant percentage of the purchase price is financed through leverage, i.e. borrowing by the acquired company.

Bootstrapping in finance refers to the method to create the spot rate curve. Operation Bootstrap (Operación Manos a la Obra) refers to the ambitious projects that industrialized Puerto Rico in the mid-20th century.

Biology

Richard Dawkins in his book River Out of Eden used the computer bootstrapping concept to explain how biological cells differentiate: "Different cells receive different combinations of chemicals, which switch on different combinations of genes, and some genes work to switch other genes on or off. And so the bootstrapping continues, until we have the full repertoire of different kinds of cells."

Phylogenetics

Bootstrapping analysis gives a way to judge the strength of support for clades on phylogenetic trees. A number is written by a node, which reflects the percentage of bootstrap trees which also resolve the clade at the endpoints of that branch.

Law

Bootstrapping is a rule preventing the admission of hearsay evidence in conspiracy cases.

Linguistics

Bootstrapping is a theory of language acquisition.

Physics

Quantum theory

Bootstrapping is using very general consistency criteria to determine the form of a quantum theory from some assumptions on the spectrum of particles or operators.

Magnetically confined fusion plasmas

In tokamak fusion devices, bootstrapping refers to the process in which a bootstrap current is self-generated by the plasma, which reduces or eliminates the need for an external current driver. Maximising the bootstrap current is a major goal of advanced tokamak designs.

Inertially confined fusion plasmas

Bootstrapping in inertial confinement fusion refers to the alpha particles produced in the fusion reaction providing further heating to the plasma. This heating leads to ignition and an overall energy gain.

Electronics

Bootstrapping is a form of positive feedback in analog circuit design.

Electric power grid

An electric power grid is almost never brought down intentionally. Generators and power stations are started and shut down as necessary. A typical power station requires power for start up prior to being able to generate power. This power is obtained from the grid, so if the entire grid is down these stations cannot be started.

Therefore, to get a grid started, there must be at least a small number of power stations that can start entirely on their own. A black start is the process of restoring a power station to operation without relying on external power. In the absence of grid power, one or more black starts are used to bootstrap the grid.

Nuclear power

A nuclear power plant always needs to have a way to remove decay heat, which is usually done with electrical cooling pumps. But in the rare case of a complete loss of electrical power, this can still be achieved by booting a turbine generator. As steam builds up in the steam generator, it can be used to power the turbine generator (initially with no oil pumps, circ water pumps, or condensation pumps). Once the turbine generator is producing electricity, the auxiliary pumps can be powered on, and the reactor cooling pumps can be run momentarily. Eventually the steam pressure will become insufficient to power the turbine generator, and the process can be shut down in reverse order. The process can be repeated until no longer needed. This can cause great damage to the turbine generator, but more importantly, it saves the nuclear reactor.

Cellular networks

A Bootstrapping Server Function (BSF) is an intermediary element in cellular networks which provides application independent functions for mutual authentication of user equipment and servers unknown to each other and for 'bootstrapping' the exchange of secret session keys afterwards. The term 'bootstrapping' is related to building a security relation with a previously unknown device first and to allow installing security elements (keys) in the device and the BSF afterwards.

Flash mob

From Wikipedia, the free encyclopedia

A public pillow fight in Bologna, Italy

A flash mob (or flashmob) is a group of people that assembles suddenly in a public place, performs for a brief time, then quickly disperses, often for the purposes of entertainment, satire, and/or artistic expression. Flash mobs may be organized via telecommunications, social media, or viral emails.

The term, coined in 2003, is generally not applied to events and performances organized for the purposes of politics (such as protests), commercial advertisement, publicity stunts that involve public relation firms, or paid professionals. In these cases of a planned purpose for the social activity in question, the term smart mobs is often applied instead.

The term "flash rob" or "flash mob robberies", a reference to the way flash mobs assemble, has been used to describe a number of robberies and assaults perpetrated suddenly by groups of teenage youth. Bill Wasik, originator of the first flash mobs, and a number of other commentators have questioned or objected to the usage of "flash mob" to describe criminal acts. Flash mob has also been featured in some Hollywood movie series, such as Step Up.

History

First flash mob

Flash mobbing was quickly imitated outside of the United States. This picture is of "sydmob" 2003, the first flash mob held in Sydney, Australia.

The first flash mobs were created in Manhattan in 2003, by Bill Wasik, senior editor of Harper's Magazine. The first attempt was unsuccessful after the targeted retail store was tipped off about the plan for people to gather. Wasik avoided such problems during the first successful flash mob, which occurred on June 17, 2003, at Macy's department store, by sending participants to preliminary staging areas—in four Manhattan bars—where they received further instructions about the ultimate event and location just before the event began.

More than 130 people converged upon the ninth-floor rug department of the store, gathering around an expensive rug. Anyone approached by a sales assistant was advised to say that the gatherers lived together in a warehouse on the outskirts of New York, that they were shopping for a "love rug", and that they made all their purchase decisions as a group. Subsequently, 200 people flooded the lobby and mezzanine of the Hyatt hotel in synchronized applause for about 15 seconds, and a shoe boutique in SoHo was invaded by participants pretending to be tourists on a bus trip.

Wasik claimed that he created flash mobs as a social experiment designed to poke fun at hippies and to highlight the cultural atmosphere of conformity and of wanting to be an insider or part of "the next big thing". The Vancouver Sun wrote, "It may have backfired on him ... [Wasik] may instead have ended up giving conformity a vehicle that allowed it to appear nonconforming." In another interview he said "the mobs started as a kind of playful social experiment meant to encourage spontaneity and big gatherings to temporarily take over commercial and public areas simply to show that they could".

Precedents and precursors

In 19th-century Tasmania, the term flash mob was used to describe a subculture consisting of female prisoners, based on the term flash language for the jargon that these women used. The 19th-century Australian term flash mob referred to a segment of society, not an event, and showed no other similarities to the modern term flash mob or the events it describes.

In 1973, the story "Flash Crowd" by Larry Niven described a concept similar to flash mobs. With the invention of popular and very inexpensive teleportation, an argument at a shopping mall—which happens to be covered by a news crew—quickly swells into a riot. In the story, broadcast coverage attracts the attention of other people, who use the widely available technology of the teleportation booth to swarm first that event—thus intensifying the riot—and then other events as they happen. Commenting on the social impact of such mobs, one character (articulating the police view) says, "We call them flash crowds, and we watch for them." In related short stories, they are named as a prime location for illegal activities (such as pickpocketing and looting) to take place. Lev Grossman suggests that the story title is a source of the term "flash mob".

People dancing at the Eutopia 15 Flashmob Event while crossing Puerta del Puente in Córdoba, Spain (2015)

Flash mobs began as a form of performance art. While they started as an apolitical act, flash mobs may share superficial similarities to political demonstrations. In the 1960s, groups such as the Yippies used street theatre to expose the public to political issues. Flash mobs can be seen as a specialized form of smart mob, a term and concept proposed by author Howard Rheingold in his 2002 book Smart Mobs: The Next Social Revolution.

Use of the term

The first documented use of the term flash mob as it is understood today was in 2003 in a blog entry posted in the aftermath of Wasik's event. The term was inspired by the earlier term smart mob.

Flash mob was added to the 11th edition of the Concise Oxford English Dictionary on July 8, 2004, where it noted it as an "unusual and pointless act" separating it from other forms of smart mobs such as types of performance, protests, and other gatherings. Also recognized noun derivatives are flash mobber and flash mobbing. Webster's New Millennium Dictionary of English defines flash mob as "a group of people who organize on the Internet and then quickly assemble in a public place, do something bizarre, and disperse." This definition is consistent with the original use of the term; however, both news media and promoters have subsequently used the term to refer to any form of smart mob, including political protests; a collaborative Internet denial of service attack; a collaborative supercomputing demonstration; and promotional appearances by pop musicians. The press has also used the term flash mob to refer to a practice in China where groups of shoppers arrange online to meet at a store in order to drive a collective bargain.

Legality

The city of Brunswick, Germany, has stopped flash mobs by strictly enforcing the already existing law of requiring a permit to use any public space for an event. In the United Kingdom, a number of flash mobs have been stopped over concerns for public health and safety. The British Transport Police have urged flash mob organizers to "refrain from holding such events at railway stations".

Crime

Referred to as flash robs, flash mob robberies, or flash robberies by the media, crimes organized by teenage youth using social media rose to international notoriety beginning in 2011. The National Retail Federation does not classify these crimes as "flash mobs" but rather "multiple offender crimes" that utilize "flash mob tactics". In a report, the NRF noted, "multiple offender crimes tend to involve groups or gangs of juveniles who already know each other, which does not earn them the term 'flash mob'." Mark Leary, a professor of psychology and neuroscience at Duke University, said that most "flash mob thuggery" involves crimes of violence that are otherwise ordinary, but are perpetrated suddenly by large, organized groups of people: "What social media adds is the ability to recruit such a large group of people, that individuals who would not rob a store or riot on their own feel freer to misbehave without being identified."

It's hard for me to believe that these kids saw some YouTube video of people Christmas caroling in a food court, and said, 'Hey, we should do that, except as a robbery!' More likely, they stumbled on the simple realization (like I did back in 2003, but like lots of other people had before and have since) that one consequence of all this technology is that you can coordinate a ton of people to show up in the same place at the same time.

— Bill Wasik

These kids are taking part in what's basically a meme. They heard about it from friends, and probably saw it on YouTube, and now they're getting their chance to participate in it themselves.

— Bill Wasik

HuffPost raised the question asking if "the media was responsible for stirring things up", and added that in some cases the local authorities did not confirm the use of social media making the "use of the term flash mob questionable". Amanda Walgrove wrote that criminals involved in such activities do not refer to themselves as "flash mobs", but that this use of the term is nonetheless appropriate. Dr. Linda Kiltz drew similar parallels between flash robs and the Occupy Movement stating, "As the use of social media increases, the potential for more flash mobs that are used for political protest and for criminal purposes is likely to increase."

Crowdsourcing

From Wikipedia, the free encyclopedia
This graphic symbolizes the use of ideas from a wide range of individuals, as used in crowdsourcing.

Crowdsourcing involves a large group of dispersed participants contributing or producing goods or services—including ideas, votes, micro-tasks, and finances—for payment or as volunteers. Contemporary crowdsourcing often involves digital platforms to attract and divide work between participants to achieve a cumulative result. Crowdsourcing is not limited to online activity, however, and there are various historical examples of crowdsourcing. The word crowdsourcing is a portmanteau of "crowd" and "outsourcing". In contrast to outsourcing, crowdsourcing usually involves less specific and more public groups of participants.

Advantages of using crowdsourcing include lowered costs, improved speed, improved quality, increased flexibility, and/or increased scalability of the work, as well as promoting diversity. Crowdsourcing methods include competitions, virtual labor markets, open online collaboration and data donation. Some forms of crowdsourcing, such as in "idea competitions" or "innovation contests" provide ways for organizations to learn beyond the "base of minds" provided by their employees (e.g. LEGO Ideas). Commercial platforms, such as Amazon Mechanical Turk, match microtasks submitted by requesters to workers who perform them. Crowdsourcing is also used by nonprofit organizations to develop common goods, such as Wikipedia.

Definitions

The term crowdsourcing was coined in 2006 by two editors at Wired, Jeff Howe and Mark Robinson, to describe how businesses were using the Internet to "outsource work to the crowd", which quickly led to the portmanteau "crowdsourcing". The Oxford English Dictionary gives a first use: "OED's earliest evidence for crowdsourcing is from 2006, in the writing of J. Howe." The online dictionary Merriam-Webster defines it as: "the practice of obtaining needed services, ideas, or content by soliciting contributions from a large group of people and especially from the online community rather than from traditional employees or suppliers."

Daren C. Brabham defined crowdsourcing as an "online, distributed problem-solving and production model." Kristen L. Guth and Brabham found that the performance of ideas offered in crowdsourcing platforms are affected not only by their quality, but also by the communication among users about the ideas, and presentation in the platform itself.

Despite the multiplicity of definitions for crowdsourcing, one constant has been the broadcasting of problems to the public, and an open call for contributions to help solve the problem. Members of the public submit solutions that are then owned by the entity who originally broadcast the problem. In some cases, the contributor of the solution is compensated monetarily with prizes or public recognition. In other cases, the only rewards may be praise or intellectual satisfaction. Crowdsourcing may produce solutions from amateurs or volunteers working in their spare time, from experts, or from small businesses.

Historical examples

While the term "crowdsourcing" was popularized online to describe Internet-based activities, some examples of projects, in retrospect, can be described as crowdsourcing.

Timeline of crowdsourcing examples

  • 618–907 – The Tang dynasty of China introduced the joint-stock company, the earliest form of crowdfunding. This was evident during the cold period of the Tang Dynasty when the colder climates resulted in poor harvests and the lessening of agricultural taxes, culminating in the fragmentation of the agricultural sector. The fragmentation meant that the government had to reform the tax system relying more on the taxation of salt and most importantly business leading to the creation of the Joint-Stock Company.
  • 1567 – King Philip II of Spain offered a cash prize for calculating the longitude of a vessel while at sea.
  • 1714 – The longitude rewards: When the British government was trying to find a way to measure a ship's longitudinal position, they offered the public a monetary prize to whoever came up with the best solution.
  • 1783 – King Louis XVI offered an award to the person who could "make the alkali" by decomposing sea salt by the "simplest and most economic method".
  • 1848 – Matthew Fontaine Maury distributed 5000 copies of his Wind and Current Charts free of charge on the condition that sailors returned a standardized log of their voyage to the U.S. Naval Observatory. By 1861, he had distributed 200,000 copies free of charge, on the same conditions.
  • 1849 – A network of some 150 volunteer weather observers all over the USA was set up as a part of the Smithsonian Institution's Meteorological Project started by the Smithsonian's first Secretary, Joseph Henry, who used the telegraph to gather volunteers' data and create a large weather map, making new information available to the public daily. For instance, volunteers tracked a tornado passing through Wisconsin and sent the findings via telegraph to the Smithsonian. Henry's project is considered the origin of what later became the National Weather Service. Within a decade, the project had more than 600 volunteer observers and had spread to Canada, Mexico, Latin America, and the Caribbean.
  • 1884 – Publication of the Oxford English Dictionary: 800 volunteers catalogued words to create the first fascicle of the OED.
  • 1916 – Planters Peanuts contest: The Mr. Peanut logo was designed by a 14-year-old boy who won the Planter Peanuts logo contest.
  • 1957 – Jørn Utzon was selected as winner of the design competition for the Sydney Opera House.
  • 1970 – French amateur photo contest C'était Paris en 1970 ("This Was Paris in 1970") was sponsored by the city of Paris, France-Inter radio, and the Fnac: 14,000 photographers produced 70,000 black-and-white prints and 30,000 color slides of the French capital to document the architectural changes of Paris. Photographs were donated to the Bibliothèque historique de la ville de Paris.
  • 1979 – Robert Axelrod invited academics on-line to submit FORTRAN algorithms to play the repeated Prisoner's Dilemma; A tit for tat algorithm ended up in first place.
  • 1991 – Linus Torvalds began work on the Linux operating system, and invited programmers around the world to contribute code.
  • 1996 – The Hollywood Stock Exchange was founded: It allowed buying and selling of shares.
  • 1997 – British rock band Marillion raised $60,000 from their fans to help finance their U.S. tour.
  • 1999 – SETI@home was launched by the University of California, Berkeley. Volunteers can contribute to searching for signals that might come from extraterrestrial intelligence by installing a program that uses idle computer time for analyzing chunks of data recorded by radio telescopes involved in the SERENDIP program.
  • 1999– The U.S. Geological Survey's (USGS's) "Did You Feel It?" website was used in the US as a method where by residents could report any tremors or shocks they felt from a recent earthquake and the approximate magnitude of the earthquake.
  • 2000 – JustGiving was established: This online platform allows the public to help raise money for charities.
  • 2000 – UNV Online Volunteering service launched: Connecting people who commit their time and skills over the Internet to help organizations address development challenges.
  • 2000 – iStockPhoto was founded: The free stock imagery website allows the public to contribute to and receive commission for their contributions.
  • 2001 – Launch of Wikipedia: "Free-access, free content Internet encyclopedia".
  • 2001 – Foundation of Topcoder – crowdsourcing software development company.
  • 2004 – OpenStreetMap, a collaborative project to create a free editable map of the world, was launched.
  • 2004 – Toyota's first "Dream car art" contest: Children were asked globally to draw their "dream car of the future".
  • 2005 – Kodak's "Go for the Gold" contest: Kodak asked anyone to submit a picture of a personal victory.
  • 2005 – Amazon Mechanical Turk (MTurk) was launched publicly on November 2, 2005. It enables businesses to hire remotely located "crowdworkers" to perform discrete on-demand tasks that computers are currently unable to do.
  • 2005 – Reddit was launched in 2005. Reddit is a social media platform and online community where users can submit, discuss and vote, leading to diverse discussions and interactions.
  • 2009 – Waze (then named FreeMap Israel), a community-oriented GPS app, was created. It allows users to submit road information and route data based on location, such as reports of car accidents or traffic, and integrates that data into its routing algorithms for all users of the app.
  • 2010 – The 1947 Partition Archive, an oral history project that asked community members around the world to document oral histories from aging witnesses of a significant but under-documented historical event, the 1947 Partition of India, was founded.
  • 2011 – Casting of Flavours (Do us a flavor in the USA) – a campaign launched by PepsiCo's Lay's in Spain. The campaign was to create a new flavor for the snack where the consumers were directly involved in its formation.

Early competitions

Crowdsourcing has often been used in the past as a competition to discover a solution. The French government proposed several of these competitions, often rewarded with Montyon Prizes. These included the Leblanc process, or the Alkali prize, where a reward was provided for separating the salt from the alkali, and the Fourneyron's turbine, when the first hydraulic commercial turbine was developed.

In response to a challenge from the French government, Nicolas Appert won a prize for inventing a new way of food preservation that involved sealing food in air-tight jars. The British government provided a similar reward to find an easy way to determine a ship's longitude in the Longitude Prize. During the Great Depression, out-of-work clerks tabulated higher mathematical functions in the Mathematical Tables Project as an outreach project. One of the largest crowdsourcing campaigns was a public design contest in 2010 hosted by the Indian government's finance ministry to create a symbol for the Indian rupee. Thousands of people sent in entries before the government zeroed in on the final symbol based on the Devanagari script using the letter Ra.

Applications

A number of motivations exist for businesses to use crowdsourcing to accomplish their tasks. These include the ability to offload peak demand, access cheap labor and information, generate better results, access a wider array of talent than what is present in one organization, and undertake problems that would have been too difficult to solve internally. Crowdsourcing allows businesses to submit problems on which contributors can work—on topics such as science, manufacturing, biotech, and medicine—optionally with monetary rewards for successful solutions. Although crowdsourcing complicated tasks can be difficult, simple work tasks can be crowdsourced cheaply and effectively.

Crowdsourcing also has the potential to be a problem-solving mechanism for government and nonprofit use. Urban and transit planning are prime areas for crowdsourcing. For example, from 2008 to 2009, a crowdsourcing project for transit planning in Salt Lake City was created to test the public participation process. Another notable application of crowdsourcing for government problem-solving is Peer-to-Patent, which was an initiative to improve patent quality in the United States through gathering public input in a structured, productive manner.

Researchers have used crowdsourcing systems such as Amazon Mechanical Turk or CloudResearch to aid their research projects by crowdsourcing some aspects of the research process, such as data collection, parsing, and evaluation to the public. Notable examples include using the crowd to create speech and language databases, to conduct user studies, and to run behavioral science surveys and experiments. Crowdsourcing systems provided researchers with the ability to gather large amounts of data, and helped researchers to collect data from populations and demographics they may not have access to locally.

Artists have also used crowdsourcing systems. In a project called the Sheep Market, Aaron Koblin used Mechanical Turk to collect 10,000 drawings of sheep from contributors around the world. Artist Sam Brown leveraged the crowd by asking visitors of his website explodingdog to send him sentences to use as inspirations for his paintings. Art curator Andrea Grover argues that individuals tend to be more open in crowdsourced projects because they are not being physically judged or scrutinized. As with other types of uses, artists use crowdsourcing systems to generate and collect data. The crowd also can be used to provide inspiration and to collect financial support for an artist's work.

In navigation systems, crowdsourcing from 100 million drivers were used by INRIX to collect users' driving times to provide better GPS routing and real-time traffic updates.

In healthcare

The use of crowdsourcing in medical and health research is increasing systematically. The process involves outsourcing tasks or gathering input from a large, diverse groups of people, often facilitated through digital platforms, to contribute to medical research, diagnostics, data analysis, promotion, and various healthcare-related initiatives. Usage of this innovative approach supplies a useful community-based method to improve medical services.

From funding individual medical cases and innovative devices to supporting research, community health initiatives, and crisis responses, crowdsourcing proves its versatile impact in addressing diverse healthcare challenges.

In 2011, UNAIDS initiated the participatory online policy project to better engage young people in decision-making processes related to AIDS. The project acquired data from 3,497 participants across seventy-nine countries through online and offline forums. The outcomes generally emphasized the importance of youth perspectives in shaping strategies to effectively address AIDS which provided a valuable insight for future community empowerment initiatives.

Another approach is sourcing results of clinical algorithms from collective input of participants. Researchers from SPIE developed a crowdsourcing tool, to train individuals, especially middle and high school students in South Korea, to diagnose malaria-infected red blood cells. Using a statistical framework, the platform combined expert diagnoses with those from minimally trained individuals, creating a gold standard library. The objective was to swiftly teach people to achieve great diagnosis accuracy without any prior training.

Cancer medicine journal conducted a review of the studies published between January 2005 and June 2016 on crowdsourcing in cancer research, with the usage PubMed, CINAHL, Scopus, PsychINFO, and Embase. All of them strongly advocate for continuous efforts to refine and expand crowdsourcing applications in academic scholarship. Analysis highlighted the importance of interdisciplinary collaborations and widespread dissemination of knowledge; the review underscored the need to fully harness crowdsourcing's potential to address challenges within cancer research.

In science

Astronomy

Crowdsourcing in astronomy was used in the early 19th century by astronomer Denison Olmsted. After being awakened in a late November night due to a meteor shower taking place, Olmsted noticed a pattern in the shooting stars. Olmsted wrote a brief report of this meteor shower in the local newspaper. "As the cause of 'Falling Stars' is not understood by meteorologists, it is desirable to collect all the facts attending this phenomenon, stated with as much precision as possible", Olmsted wrote to readers, in a report subsequently picked up and pooled to newspapers nationwide. Responses came pouring in from many states, along with scientists' observations sent to the American Journal of Science and Arts. These responses helped him to make a series of scientific breakthroughs including observing the fact that meteor showers are seen nationwide and fall from space under the influence of gravity. The responses also allowed him to approximate a velocity for the meteors.

A more recent version of crowdsourcing in astronomy is NASA's photo organizing project, which asked internet users to browse photos taken from space and try to identify the location the picture is documenting.

Behavioral science

In the field of behavioral science, crowdsourcing is often used to gather data and insights on human behavior and decision making. Researchers may create online surveys or experiments that are completed by a large number of participants, allowing them to collect a diverse and potentially large amount of data. Crowdsourcing can also be used to gather real-time data on behavior, such as through the use of mobile apps that track and record users' activities and decision making. The use of crowdsourcing in behavioral science has the potential to greatly increase the scope and efficiency of research, and has been used in studies on topics such as psychology research, political attitudes, and social media use.

Energy system research

Energy system models require large and diverse datasets, increasingly so given the trend towards greater temporal and spatial resolution. In response, there have been several initiatives to crowdsource this data. Launched in December 2009, OpenEI is a collaborative website run by the US government that provides open energy data. While much of its information is from US government sources, the platform also seeks crowdsourced input from around the world. The semantic wiki and database Enipedia also publishes energy systems data using the concept of crowdsourced open information. Enipedia went live in March 2011.

Genealogy research

Genealogical research used crowdsourcing techniques long before personal computers were common. Beginning in 1942, members of the Church of Jesus Christ of Latter-day Saints encouraged members to submit information about their ancestors. The submitted information was gathered together into a single collection. In 1969, to encourage more participation, the church started the three-generation program. In this program, church members were asked to prepare documented family group record forms for the first three generations. The program was later expanded to encourage members to research at least four generations and became known as the four-generation program.

Institutes that have records of interest to genealogical research have used crowds of volunteers to create catalogs and indices to records.

Genetic genealogy research

Genetic genealogy is a combination of traditional genealogy with genetics. The rise of personal DNA testing, after the turn of the century, by companies such as Gene by Gene, FTDNA, GeneTree, 23andMe, and Ancestry.com, has led to public and semi public databases of DNA testing using crowdsourcing techniques. Citizen science projects have included support, organization, and dissemination of personal DNA (genetic) testing. Similar to amateur astronomy, citizen scientists encouraged by volunteer organizations like the International Society of Genetic Genealogy have provided valuable information and research to the professional scientific community. The Genographic Project, which began in 2005, is a research project carried out by the National Geographic Society's scientific team to reveal patterns of human migration using crowdsourced DNA testing and reporting of results.

Ornithology

Another early example of crowdsourcing occurred in the field of ornithology. On 25 December 1900, Frank Chapman, an early officer of the National Audubon Society, initiated a tradition dubbed the "Christmas Day Bird Census". The project called birders from across North America to count and record the number of birds in each species they witnessed on Christmas Day. The project was successful, and the records from 27 different contributors were compiled into one bird census, which tallied around 90 species of birds. This large-scale collection of data constituted an early form of citizen science, the premise upon which crowdsourcing is based. In the 2012 census, more than 70,000 individuals participated across 2,369 bird count circles. Christmas 2014 marked the National Audubon Society's 115th annual Christmas Bird Count.

Seismology

The European-Mediterranean Seismological Centre (EMSC) has developed a seismic detection system by monitoring the traffic peaks on its website and analyzing keywords used on Twitter.

In journalism

Crowdsourcing is increasingly used in professional journalism. Journalists are able to organize crowdsourced information by fact checking the information, and then using the information they have gathered in their articles as they see fit. A daily newspaper in Sweden has successfully used crowdsourcing in investigating the home loan interest rates in the country in 2013–2014, which resulted in over 50,000 submissions. A daily newspaper in Finland crowdsourced an investigation into stock short-selling in 2011–2012, and the crowdsourced information led to revelations of a tax evasion system by a Finnish bank. The bank executive was fired and policy changes followed. TalkingPointsMemo in the United States asked its readers to examine 3,000 emails concerning the firing of federal prosecutors in 2008. The British newspaper The Guardian crowdsourced the examination of hundreds of thousands of documents in 2009.

Data donation

Data donation is a crowdsourcing approach to gather digital data. It is used by researchers and organizations to gain access to data from online platforms, websites, search engines and apps and devices. Data donation projects usually rely on participants volunteering their authentic digital profile information. Examples include:

  • DataSkop developed by Algorithm Watch, a non-profit research organization in Germany, which accessed data on social media algorithms and automated decision-making systems.
  • Mozilla Rally, from the Mozilla Foundation, is a browser extension for adult participants in the US to provide access to their data for research projects.
  • The Australian Search Experience and Ad Observatory projects set up in 2021 by researchers at the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) in Australia was using data donations to analyze how Google personalized search results, and examine how Facebook's algorithmic advertising model worked.
  • The Citizen Browser Project, developed by The Markup, was designed to measure how disinformation traveled across social media platforms over time.
  • Large Emergency Event Digital Information Repository was an effort to create a repository for images and videos from natural disasters, terrorist, and criminal events

In public policy

Crowdsourcing public policy and the production of public services is also referred to as citizen sourcing. While some scholars argue crowdsourcing for this purpose as a policy tool or a definite means of co-production, others question that and argue that crowdsourcing should be considered just as a technological enabler that simply increases speed and ease of participation. Crowdsourcing can also play a role in democratization.

The first conference focusing on Crowdsourcing for Politics and Policy took place at Oxford University, under the auspices of the Oxford Internet Institute in 2014. Research has emerged since 2012 which focused on the use of crowdsourcing for policy purposes. These include experimentally investigating the use of Virtual Labor Markets for policy assessment, and assessing the potential for citizen involvement in process innovation for public administration.

Governments across the world are increasingly using crowdsourcing for knowledge discovery and civic engagement. Iceland crowdsourced their constitution reform process in 2011, and Finland has crowdsourced several law reform processes to address their off-road traffic laws. The Finnish government allowed citizens to go on an online forum to discuss problems and possible resolutions regarding some off-road traffic laws. The crowdsourced information and resolutions would then be passed on to legislators to refer to when making a decision, allowing citizens to contribute to public policy in a more direct manner. Palo Alto crowdsources feedback for its Comprehensive City Plan update in a process started in 2015. The House of Representatives in Brazil has used crowdsourcing in policy-reforms.

NASA used crowdsourcing to analyze large sets of images. As part of the Open Government Initiative of the Obama Administration, the General Services Administration collected and amalgamated suggestions for improving federal websites.

For part of the Obama and Trump Administrations, the We the People system collected signatures on petitions, which were entitled to an official response from the White House once a certain number had been reached. Several U.S. federal agencies ran inducement prize contests, including NASA and the Environmental Protection Agency.

Language-related data

Crowdsourcing has been used extensively for gathering language-related data.

For dictionary work, crowdsourcing was applied over a hundred years ago by the Oxford English Dictionary editors using paper and postage. It has also been used for collecting examples of proverbs on a specific topic (e.g. religious pluralism) for a printed journal. Crowdsourcing language-related data online has proven very effective and many dictionary compilation projects used crowdsourcing. It is used particularly for specialist topics and languages that are not well documented, such as for the Oromo language. Software programs have been developed for crowdsourced dictionaries, such as WeSay. A slightly different form of crowdsourcing for language data was the online creation of scientific and mathematical terminology for American Sign Language.

In linguistics, crowdsourcing strategies have been applied to estimate word knowledge, vocabulary size, and word origin. Implicit crowdsourcing on social media has also approximating sociolinguistic data efficiently. Reddit conversations in various location-based subreddits were analyzed for the presence of grammatical forms unique to a regional dialect. These were then used to map the extent of the speaker population. The results could roughly approximate large-scale surveys on the subject without engaging in field interviews.

Mining publicly available social media conversations can be used as a form of implicit crowdsourcing to approximate the geographic extent of speaker dialects. Proverb collection is also being done via crowdsourcing on the Web, most notably for the Pashto language of Afghanistan and Pakistan. Crowdsourcing has been extensively used to collect high-quality gold standards for creating automatic systems in natural language processing (e.g. named entity recognition, entity linking).

In product design

LEGO allows users to work on new product designs while conducting requirements testing. Any user can provide a design for a product, and other users can vote on the product. Once the submitted product has received 10,000 votes, it will be formally reviewed in stages and go into production with no impediments such as legal flaws identified. The creator receives royalties from the net income. Labelling new products as "customer-ideated" through crowdsourcing initiatives, as opposed to not specifying the source of design, leads to a substantial increase in the actual market performance of the products. Merely highlighting the source of design to customers, particularly, attributing the product to crowdsourcing efforts from user communities, can lead to a significant boost in product sales. Consumers perceive "customer-ideated" products as more effective in addressing their needs, leading to a quality inference. The design mode associated with crowdsourced ideas is considered superior in generating promising new products, contributing to the observed increase in market performance.

In business

Homeowners can use Airbnb to list their accommodation or unused rooms. Owners set their own nightly, weekly and monthly rates and accommodations. The business, in turn, charges guests and hosts a fee. Guests usually end up spending between $9 and $15. They have to pay a booking fee every time they book a room. The landlord, in turn, pays a service fee for the amount due. The company has 1,500 properties in 34,000 cities in more than 190 countries.

In market research

Crowdsourcing is frequently used in market research as a way to gather insights and opinions from a large number of consumers. Companies may create online surveys or focus groups that are open to the general public, allowing them to gather a diverse range of perspectives on their products or services. This can be especially useful for companies seeking to understand the needs and preferences of a particular market segment or to gather feedback on the effectiveness of their marketing efforts. The use of crowdsourcing in market research allows companies to quickly and efficiently gather a large amount of data and insights that can inform their business decisions.

Other examples

  • GeographyVolunteered geographic information (VGI) is geographic information generated through crowdsourcing, as opposed to traditional methods of Professional Geographic Information (PGI). In describing the built environment, VGI has many advantages over PGI, primarily perceived currency, accuracy and authority. OpenStreetMap is an example of crowdsourced mapping project.
  • Engineering — Many companies are introducing crowdsourcing to grow their engineering capabilities and find solutions to unsolved technical challenges and the need to adopt newest technologies such as 3D printing and the IOT.
  • Libraries, museums and archives — Newspaper text correction at the National Library of Australia was an early, influential example of work with text transcriptions for crowdsourcing in cultural heritage institutions. The Steve Museum project provided a prototype for categorizing artworks. Crowdsourcing is used in libraries for OCR corrections on digitized texts, for tagging and for funding, especially in the absence of financial and human means. Volunteers can contribute explicitly with conscious effort or implicitly without being known by turning the text on the raw newspaper image into human corrected digital form.
  • Agriculture — Crowdsource research also applies to the field of agriculture. Crowdsourcing can be used to help farmers and experts to dentify different types of weeds from the fields and also to provide assistance in removing the weeds.
  • Cheating in bridgeBoye Brogeland initiated a crowdsourcing investigation of cheating by top-level bridge players that showed several players as guilty, which led to their suspension.
  • Open-source software and Crowdsourcing software development have been used extensively in the domain of software development.
  • Healthcare — Research has emerged that outlined the use of crowdsourcing techniques in the public health domain. The collective intelligence outcomes from crowdsourcing are being generated in three broad categories of public health care: health promotion, health research, and health maintenance. Crowdsourcing also enables researchers to move from small homogeneous groups of participants to large heterogenous groups beyond convenience samples such as students or higher educated people. The SESH group focuses on using crowdsourcing to improve health.

Methods

Internet and digital technologies have massively expanded the opportunities for crowdsourcing. However, the effect of user communication and platform presentation can have a major bearing on the success of an online crowdsourcing project. The crowdsourced problem can range from huge tasks (such as finding alien life or mapping earthquake zones) or very small (identifying images). Some examples of successful crowdsourcing themes are problems that bug people, things that make people feel good about themselves, projects that tap into niche knowledge of proud experts, and subjects that people find sympathetic.

Crowdsourcing can either take an explicit or an implicit route:

  • Explicit crowdsourcing lets users work together to evaluate, share, and build different specific tasks, while implicit crowdsourcing means that users solve a problem as a side effect of something else they are doing. With explicit crowdsourcing, users can evaluate particular items like books or webpages, or share by posting products or items. Users can also build artifacts by providing information and editing other people's work.
  • Implicit crowdsourcing can take two forms: standalone and piggyback. Standalone allows people to solve problems as a side effect of the task they are actually doing, whereas piggyback takes users' information from a third-party website to gather information. This is also known as data donation.

In his 2013 book, Crowdsourcing, Daren C. Brabham puts forth a problem-based typology of crowdsourcing approaches:

  • Knowledge discovery and management is used for information management problems where an organization mobilizes a crowd to find and assemble information. It is ideal for creating collective resources.
  • Distributed human intelligence tasking (HIT) is used for information management problems where an organization has a set of information in hand and mobilizes a crowd to process or analyze the information. It is ideal for processing large data sets that computers cannot easily do. Amazon Mechanical Turk uses this approach.
  • Broadcast search is used for ideation problems where an organization mobilizes a crowd to come up with a solution to a problem that has an objective, provable right answer. It is ideal for scientific problem-solving.
  • Peer-vetted creative production is used for ideation problems, where an organization mobilizes a crowd to come up with a solution to a problem which has an answer that is subjective or dependent on public support. It is ideal for design, aesthetic, or policy problems.

Ivo Blohm identifies four types of Crowdsourcing Platforms: Microtasking, Information Pooling, Broadcast Search, and Open Collaboration. They differ in the diversity and aggregation of contributions that are created. The diversity of information collected can either be homogenous or heterogenous. The aggregation of information can either be selective or integrative. Some common categories of crowdsourcing have been used effectively in the commercial world include crowdvoting, crowdsolving, crowdfunding, microwork, creative crowdsourcing, crowdsource workforce management, and inducement prize contests.

Crowdvoting

Crowdvoting occurs when a website gathers a large group's opinions and judgments on a certain topic. Some crowdsourcing tools and platforms allow participants to rank each other's contributions, e.g. in answer to the question "What is one thing we can do to make Acme a great company?" One common method for ranking is "like" counting, where the contribution with the most "like" votes ranks first. This method is simple and easy to understand, but it privileges early contributions, which have more time to accumulate votes. In recent years, several crowdsourcing companies have begun to use pairwise comparisons backed by ranking algorithms. Ranking algorithms do not penalize late contributions. They also produce results quicker. Ranking algorithms have proven to be at least 10 times faster than manual stack ranking. One drawback, however, is that ranking algorithms are more difficult to understand than vote counting.

The Iowa Electronic Market is a prediction market that gathers crowds' views on politics and tries to ensure accuracy by having participants pay money to buy and sell contracts based on political outcomes. Some of the most famous examples have made use of social media channels: Domino's Pizza, Coca-Cola, Heineken, and Sam Adams have crowdsourced a new pizza, bottle design, beer, and song respectively. A website called Threadless selected the T-shirts it sold by having users provide designs and vote on the ones they like, which are then printed and available for purchase.

The California Report Card (CRC), a program jointly launched in January 2014 by the Center for Information Technology Research in the Interest of Society and Lt. Governor Gavin Newsom, is an example of modern-day crowd voting. Participants access the CRC online and vote on six timely issues. Through principal component analysis, the users are then placed into an online "café" in which they can present their own political opinions and grade the suggestions of other participants. This system aims to effectively involve the greater public in relevant political discussions and highlight the specific topics with which people are most concerned.

Crowdvoting's value in the movie industry was shown when in 2009 a crowd accurately predicted the success or failure of a movie based on its trailer, a feat that was replicated in 2013 by Google.

On Reddit, users collectively rate web content, discussions and comments as well as questions posed to persons of interest in "AMA" and AskScience online interviews.

In 2017, Project Fanchise purchased a team in the Indoor Football League and created the Salt Lake Screaming Eagles, a fan run team. Using a mobile app, the fans voted on the day-to-day operations of the team, the mascot name, signing of players and even offensive play calling during games.

Crowdfunding

Crowdfunding is the process of funding projects by a multitude of people contributing a small amount to attain a certain monetary goal, typically via the Internet. Crowdfunding has been used for both commercial and charitable purposes. The crowdfuding model that has been around the longest is rewards-based crowdfunding. This model is where people can prepurchase products, buy experiences, or simply donate. While this funding may in some cases go towards helping a business, funders are not allowed to invest and become shareholders via rewards-based crowdfunding.

Individuals, businesses, and entrepreneurs can showcase their businesses and projects by creating a profile, which typically includes a short video introducing their project, a list of rewards per donation, and illustrations through images. Funders make monetary contribution for numerous reasons:

  1. They connect to the greater purpose of the campaign, such as being a part of an entrepreneurial community and supporting an innovative idea or product.
  2. They connect to a physical aspect of the campaign like rewards and gains from investment.
  3. They connect to the creative display of the campaign's presentation.
  4. They want to see new products before the public.

The dilemma for equity crowdfunding in the US as of 2012 was during a refinement process for the regulations of the Securities and Exchange Commission, which had until 1 January 2013 to tweak the fundraising methods. The regulators were overwhelmed trying to regulate Dodd-Frank and all the other rules and regulations involving public companies and the way they traded. Advocates of regulation claimed that crowdfunding would open up the flood gates for fraud, called it the "wild west" of fundraising, and compared it to the 1980s days of penny stock "cold-call cowboys". The process allowed for up to $1 million to be raised without some of the regulations being involved. Companies under the then-current proposal would have exemptions available and be able to raise capital from a larger pool of persons, which can include lower thresholds for investor criteria, whereas the old rules required that the person be an "accredited" investor. These people are often recruited from social networks, where the funds can be acquired from an equity purchase, loan, donation, or ordering. The amounts collected have become quite high, with requests that are over a million dollars for software such as Trampoline Systems, which used it to finance the commercialization of their new software.

Inducement prize contests

Web-based idea competitions or inducement prize contests often consist of generic ideas, cash prizes, and an Internet-based platform to facilitate easy idea generation and discussion. An example of these competitions includes an event like IBM's 2006 "Innovation Jam", attended by over 140,000 international participants and yielded around 46,000 ideas. Another example is the Netflix Prize in 2009. People were asked to come up with a recommendation algorithm that is more accurate than Netflix's current algorithm. It had a grand prize of US$1,000,000, and it was given to a team which designed an algorithm that beat Netflix's own algorithm for predicting ratings by 10.06%.

Another example of competition-based crowdsourcing is the 2009 DARPA balloon experiment, where DARPA placed 10 balloon markers across the United States and challenged teams to compete to be the first to report the location of all the balloons. A collaboration of efforts was required to complete the challenge quickly and in addition to the competitive motivation of the contest as a whole, the winning team (MIT, in less than nine hours) established its own "collaborapetitive" environment to generate participation in their team. A similar challenge was the Tag Challenge, funded by the US State Department, which required locating and photographing individuals in five cities in the US and Europe within 12 hours based only on a single photograph. The winning team managed to locate three suspects by mobilizing volunteers worldwide using a similar incentive scheme to the one used in the balloon challenge.

Using open innovation platforms is an effective way to crowdsource people's thoughts and ideas for research and development. The company InnoCentive is a crowdsourcing platform for corporate research and development where difficult scientific problems are posted for crowds of solvers to discover the answer and win a cash prize that ranges from $10,000 to $100,000 per challenge. InnoCentive, of Waltham, Massachusetts, and London, England, provides access to millions of scientific and technical experts from around the world. The company claims a success rate of 50% in providing successful solutions to previously unsolved scientific and technical problems. The X Prize Foundation creates and runs incentive competitions offering between $1 million and $30 million for solving challenges. Local Motors is another example of crowdsourcing, and it is a community of 20,000 automotive engineers, designers, and enthusiasts that compete to build off-road rally trucks.

Implicit crowdsourcing

Implicit crowdsourcing is less obvious because users do not necessarily know they are contributing, yet can still be very effective in completing certain tasks. Rather than users actively participating in solving a problem or providing information, implicit crowdsourcing involves users doing another task entirely where a third party gains information for another topic based on the user's actions.

A good example of implicit crowdsourcing is the ESP game, where users find words to describe Google images, which are then used as metadata for the images. Another popular use of implicit crowdsourcing is through reCAPTCHA, which asks people to solve CAPTCHAs to prove they are human, and then provides CAPTCHAs from old books that cannot be deciphered by computers, to digitize them for the web. Like many tasks solved using the Mechanical Turk, CAPTCHAs are simple for humans, but often very difficult for computers.

Piggyback crowdsourcing can be seen most frequently by websites such as Google that data-mine a user's search history and websites to discover keywords for ads, spelling corrections, and finding synonyms. In this way, users are unintentionally helping to modify existing systems, such as Google Ads.

Other types

  • Creative crowdsourcing involves sourcing people for creative projects such as graphic design, crowdsourcing architecture, product design, apparel design, movies, writing, company naming, illustration, etc. While crowdsourcing competitions have been used for decades in some creative fields such as architecture, creative crowdsourcing has proliferated with the recent development of web-based platforms where clients can solicit a wide variety of creative work at lower cost than by traditional means.
  • Crowdshipping (crowd-shipping) is a peer-to-peer shipping service, usually conducted via an online platform or marketplace. There are several methods that have been categorized as crowd-shipping:
    • Travelers heading in the direction of the buyer, and are willing to bring the package as part of their luggage for a reward.
    • Truck drivers whose route lies along the buyer's location and who are willing to take extra items in their truck.
    • Community-based platforms that connect international buyers and local forwarders, by allowing buyers to use forwarder's address as purchase destination, after which forwarders ship items further to the buyer.
  • Crowdsolving is a collaborative and holistic way of solving a problem through many people, communities, groups, or resources. It is a type of crowdsourcing with focus on complex and intellectually demanding problems requiring considerable effort, and the quality or uniqueness of contribution.
    • Problem–idea chains are a form of idea crowdsourcing and crowdsolving, where individuals are asked to submit ideas to solve problems and then problems that can be solved with those ideas. The aim is to find encourage individuals to find practical solutions to problems that are well thought through.
  • Macrowork tasks typically have these characteristics: they can be done independently, they take a fixed amount of time, and they require special skills. Macro-tasks could be part of specialized projects or could be part of a large, visible project where workers pitch in wherever they have the required skills. The key distinguishing factors are that macro-work requires specialized skills and typically takes longer, while microwork requires no specialized skills.
  • Microwork is a crowdsourcing platform that allows users to do small tasks for which computers lack aptitude in for low amounts of money. Amazon's Mechanical Turk has created many different projects for users to participate in, where each task requires very little time and offers a very small amount in payment. When choosing tasks, since only certain users "win", users learn to submit later and pick less popular tasks to increase the likelihood of getting their work chosen. An example of a Mechanical Turk project is when users searched satellite images for a boat to find Jim Gray, a missing computer scientist.
  • Mobile crowdsourcing involves activities that take place on smartphones or mobile platforms that are frequently characterized by GPS technology. This allows for real-time data gathering and gives projects greater reach and accessibility. However, mobile crowdsourcing can lead to an urban bias, and can have safety and privacy concerns.
  • Simple projects are those that require a large amount of time and skills compared to micro and macro-work. While an example of macro-work would be writing survey feedback, simple projects rather include activities like writing a basic line of code or programming a database, which both require a larger time commitment and skill level. These projects are usually not found on sites like Amazon Mechanical Turk, and are rather posted on platforms like Upwork that call for a specific expertise.
  • Complex projects generally take the most time, have higher stakes, and call for people with very specific skills. These are generally "one-off" projects that are difficult to accomplish and can include projects such as designing a new product that a company hopes to patent. Such projects are considered to be complex because design is a meticulous process that requires a large amount of time to perfect, and people completing the project must have specialized training in design to effectively complete the project. These projects usually pay the highest, yet are rarely offered.

Demographics of the crowd

The crowd is an umbrella term for the people who contribute to crowdsourcing efforts. Though it is sometimes difficult to gather data about the demographics of the crowd as a whole, several studies have examined various specific online platforms. Amazon Mechanical Turk has received a great deal of attention in particular. A study in 2008 by Ipeirotis found that users at that time were primarily American, young, female, and well-educated, with 40% earning more than $40,000 per year. In November 2009, Ross found a very different Mechanical Turk population where 36% of which was Indian. Two-thirds of Indian workers were male, and 66% had at least a bachelor's degree. Two-thirds had annual incomes less than $10,000, with 27% sometimes or always depending on income from Mechanical Turk to make ends meet. More recent studies have found that U.S. Mechanical Turk workers are approximately 58% female, and nearly 67% of workers are in their 20s and 30s. Close to 80% are White, and 9% are Black. MTurk workers are less likely to be married or have children as compared to the general population. In the US population over 18, 45% are unmarried, while the proportion of unmarried workers on MTurk is around 57%. Additionally, about 55% of MTurk workers do not have any children, which is significantly higher than the general population. Approximately 68% of U.S. workers are employed, compared to 60% in the general population. MTurk workers in the U.S. are also more likely to have a four-year college degree (35%) compared to the general population (27%). Politics within the U.S. sample of MTurk are skewed liberal, with 46% Democrats, 28% Republicans, and 26%  "other". MTurk workers are also less religious than the U.S. population, with 41% religious, 20% spiritual, 21% agnostic, and 16% atheist.

The demographics of Microworkers.com differ from Mechanical Turk in that the US and India together accounting for only 25% of workers; 197 countries are represented among users, with Indonesia (18%) and Bangladesh (17%) contributing the largest share. However, 28% of employers are from the US.

Another study of the demographics of the crowd at iStockphoto found a crowd that was largely white, middle- to upper-class, higher educated, worked in a so-called "white-collar job" and had a high-speed Internet connection at home. In a crowd-sourcing diary study of 30 days in Europe, the participants were predominantly higher educated women.

Studies have also found that crowds are not simply collections of amateurs or hobbyists. Rather, crowds are often professionally trained in a discipline relevant to a given crowdsourcing task and sometimes hold advanced degrees and many years of experience in the profession. Claiming that crowds are amateurs, rather than professionals, is both factually untrue and may lead to marginalization of crowd labor rights.

Gregory Saxton et al. studied the role of community users, among other elements, during his content analysis of 103 crowdsourcing organizations. They developed a taxonomy of nine crowdsourcing models (intermediary model, citizen media production, collaborative software development, digital goods sales, product design, peer-to-peer social financing, consumer report model, knowledge base building model, and collaborative science project model) in which to categorize the roles of community users, such as researcher, engineer, programmer, journalist, graphic designer, etc., and the products and services developed.

Motivations

Contributors

Many researchers suggest that both intrinsic and extrinsic motivations cause people to contribute to crowdsourced tasks and these factors influence different types of contributors. For example, people employed in a full-time position rate human capital advancement as less important than part-time workers do, while women rate social contact as more important than men do.

Intrinsic motivations are broken down into two categories: enjoyment-based and community-based motivations. Enjoyment-based motivations refer to motivations related to the fun and enjoyment contributors experience through their participation. These motivations include: skill variety, task identity, task autonomy, direct feedback from the job, and taking the job as a pastime. Community-based motivations refer to motivations related to community participation, and include community identification and social contact. In crowdsourced journalism, the motivation factors are intrinsic: the crowd is driven by a possibility to make social impact, contribute to social change, and help their peers.

Extrinsic motivations are broken down into three categories: immediate payoffs, delayed payoffs, and social motivations. Immediate payoffs, through monetary payment, are the immediately received compensations given to those who complete tasks. Delayed payoffs are benefits that can be used to generate future advantages, such as training skills and being noticed by potential employers. Social motivations are the rewards of behaving pro-socially, such as the altruistic motivations of online volunteers. Chandler and Kapelner found that US users of the Amazon Mechanical Turk were more likely to complete a task when told they were going to help researchers identify tumor cells, than when they were not told the purpose of their task. However, of those who completed the task, quality of output did not depend on the framing.

Motivation in crowdsourcing is often a mix of intrinsic and extrinsic factors. In a crowdsourced law-making project, the crowd was motivated by both intrinsic and extrinsic factors. Intrinsic motivations included fulfilling civic duty, affecting the law for sociotropic reasons, to deliberate with and learn from peers. Extrinsic motivations included changing the law for financial gain or other benefits. Participation in crowdsourced policy-making was an act of grassroots advocacy, whether to pursue one's own interest or more altruistic goals, such as protecting nature. Participants in online research studies report their motivation as both intrinsic enjoyment and monetary gain.

Another form of social motivation is prestige or status. The International Children's Digital Library recruited volunteers to translate and review books. Because all translators receive public acknowledgment for their contributions, Kaufman and Schulz cite this as a reputation-based strategy to motivate individuals who want to be associated with institutions that have prestige. The Mechanical Turk uses reputation as a motivator in a different sense, as a form of quality control. Crowdworkers who frequently complete tasks in ways judged to be inadequate can be denied access to future tasks, whereas workers who pay close attention may be rewarded by gaining access to higher-paying tasks or being on an "Approved List" of workers. This system may incentivize higher-quality work. However, this system only works when requesters reject bad work, which many do not.

Despite the potential global reach of IT applications online, recent research illustrates that differences in location affect participation outcomes in IT-mediated crowds.

Limitations and controversies

At least six major topics cover the limitations and controversies about crowdsourcing:

  1. Impact of crowdsourcing on product quality
  2. Entrepreneurs contribute less capital themselves
  3. Increased number of funded ideas
  4. The value and impact of the work received from the crowd
  5. The ethical implications of low wages paid to workers
  6. Trustworthiness and informed decision making

Impact of crowdsourcing on product quality

Crowdsourcing allows anyone to participate, allowing for many unqualified participants and resulting in large quantities of unusable contributions. Companies, or additional crowdworkers, then have to sort through the low-quality contributions. The task of sorting through crowdworkers' contributions, along with the necessary job of managing the crowd, requires companies to hire actual employees, thereby increasing management overhead. For example, susceptibility to faulty results can be caused by targeted, malicious work efforts. Since crowdworkers completing microtasks are paid per task, a financial incentive often causes workers to complete tasks quickly rather than well. Verifying responses is time-consuming, so employers often depend on having multiple workers complete the same task to correct errors. However, having each task completed multiple times increases time and monetary costs. Some companies, like CloudResearch, control data quality by repeatedly vetting crowdworkers to ensure they are paying attention and providing high-quality work.

Crowdsourcing quality is also impacted by task design. Lukyanenko et al. argue that, the prevailing practice of modeling crowdsourcing data collection tasks in terms of fixed classes (options), unnecessarily restricts quality. Results demonstrate that information accuracy depends on the classes used to model domains, with participants providing more accurate information when classifying phenomena at a more general level (which is typically less useful to sponsor organizations, hence less common). Further, greater overall accuracy is expected when participants could provide free-form data compared to tasks in which they select from constrained choices. In behavioral science research, it is often recommended to include open-ended responses, in addition to other forms of attention checks, to assess data quality.

Just as limiting, oftentimes there is not enough skills or expertise in the crowd to successfully accomplish the desired task. While this scenario does not affect "simple" tasks such as image labeling, it is particularly problematic for more complex tasks, such as engineering design or product validation. A comparison between the evaluation of business models from experts and an anonymous online crowd showed that an anonymous online crowd cannot evaluate business models to the same level as experts. In these cases, it may be difficult or even impossible to find qualified people in the crowd, as their responses represent only a small fraction of the workers compared to consistent, but incorrect crowd members. However, if the task is "intermediate" in its difficulty, estimating crowdworkers' skills and intentions and leveraging them for inferring true responses works well, albeit with an additional computation cost.

Crowdworkers are a nonrandom sample of the population. Many researchers use crowdsourcing to quickly and cheaply conduct studies with larger sample sizes than would be otherwise achievable. However, due to limited access to the Internet, participation in low developed countries is relatively low. Participation in highly developed countries is similarly low, largely because the low amount of pay is not a strong motivation for most users in these countries. These factors lead to a bias in the population pool towards users in medium developed countries, as deemed by the human development index. Participants in these countries sometimes masquerade as U.S. participants to gain access to certain tasks. This led to the "bot scare" on Amazon Mechanical Turk in 2018, when researchers thought bots were completing research surveys due to the lower quality of responses originating from medium-developed countries.

The likelihood that a crowdsourced project will fail due to lack of monetary motivation or too few participants increases over the course of the project. Tasks that are not completed quickly may be forgotten, buried by filters and search procedures. This results in a long-tail power law distribution of completion times. Additionally, low-paying research studies online have higher rates of attrition, with participants not completing the study once started. Even when tasks are completed, crowdsourcing does not always produce quality results. When Facebook began its localization program in 2008, it encountered some criticism for the low quality of its crowdsourced translations. One of the problems of crowdsourcing products is the lack of interaction between the crowd and the client. Usually little information is known about the final product, and workers rarely interacts with the final client in the process. This can decrease the quality of product as client interaction is considered to be a vital part of the design process.

An additional cause of the decrease in product quality that can result from crowdsourcing is the lack of collaboration tools. In a typical workplace, coworkers are organized in such a way that they can work together and build upon each other's knowledge and ideas. Furthermore, the company often provides employees with the necessary information, procedures, and tools to fulfill their responsibilities. However, in crowdsourcing, crowd-workers are left to depend on their own knowledge and means to complete tasks.

A crowdsourced project is usually expected to be unbiased by incorporating a large population of participants with a diverse background. However, most of the crowdsourcing works are done by people who are paid or directly benefit from the outcome (e.g. most of open source projects working on Linux). In many other cases, the end product is the outcome of a single person's endeavor, who creates the majority of the product, while the crowd only participates in minor details.

Entrepreneurs contribute less capital themselves

To make an idea turn into a reality, the first component needed is capital. Depending on the scope and complexity of the crowdsourced project, the amount of necessary capital can range from a few thousand dollars to hundreds of thousands, if not more. The capital-raising process can take from days to months depending on different variables, including the entrepreneur's network and the amount of initial self-generated capital.

The crowdsourcing process allows entrepreneurs to access a wide range of investors who can take different stakes in the project. As an effect, crowdsourcing simplifies the capital-raising process and allows entrepreneurs to spend more time on the project itself and reaching milestones rather than dedicating time to get it started. Overall, the simplified access to capital can save time to start projects and potentially increase the efficiency of projects.

Others argue that easier access to capital through a large number of smaller investors can hurt the project and its creators. With a simplified capital-raising process involving more investors with smaller stakes, investors are more risk-seeking because they can take on an investment size with which they are comfortable. This leads to entrepreneurs losing possible experience convincing investors who are wary of potential risks in investing because they do not depend on one single investor for the survival of their project. Instead of being forced to assess risks and convince large institutional investors on why their project can be successful, wary investors can be replaced by others who are willing to take on the risk.

Some translation companies and translation tool consumers pretend to use crowdsourcing as a means for drastically cutting costs, instead of hiring professional translators. This situation has been systematically denounced by IAPTI and other translator organizations.

Increased number of funded ideas

The raw number of ideas that get funded and the quality of the ideas is a large controversy over the issue of crowdsourcing.

Proponents argue that crowdsourcing is beneficial because it allows the formation of startups with niche ideas that would not survive venture capitalist or angel funding, which areoftentimes the primary investors in startups. Many ideas are scrapped in their infancy due to insufficient support and lack of capital, but crowdsourcing allows these ideas to be started if an entrepreneur can find a community to take interest in the project.

Crowdsourcing allows those who would benefit from the project to fund and become a part of it, which is one way for small niche ideas get started. However, when the number of projects grows, the number of failures also increases. Crowdsourcing assists the development of niche and high-risk projects due to a perceived need from a select few who seek the product. With high risk and small target markets, the pool of crowdsourced projects faces a greater possible loss of capital, lower return, and lower levels of success.[221]

Labor-related concerns

Because crowdworkers are considered independent contractors rather than employees, they are not guaranteed minimum wage. In practice, workers using Amazon Mechanical Turk generally earn less than minimum wage. In 2009, it was reported that United States Turk users earned an average of $2.30 per hour for tasks, while users in India earned an average of $1.58 per hour, which is below minimum wage in the United States (but not in India).[179][222] In 2018, a survey of 2,676 Amazon Mechanical Turk workers doing 3.8 million tasks found that the median hourly wage was approximately $2 per hour, and only 4% of workers earned more than the federal minimum wage of $7.25 per hour.[223] Some researchers who have considered using Mechanical Turk to get participants for research studies have argued that the wage conditions might be unethical.[55][224] However, according to other research, workers on Amazon Mechanical Turk do not feel they are exploited and are ready to participate in crowdsourcing activities in the future.[225] A more recent study using stratified random sampling to access a representative sample of Mechanical Turk workers found that the U.S. MTurk population is financially similar to the general population.[181] Workers tend to participate in tasks as a form of paid leisure and to supplement their primary income, and only 7% view it as a full-time job. Overall, workers rated MTurk as less stressful than other jobs. Workers also earn more than previously reported, about $6.50 per hour. They see MTurk as part of the solution to their financial situation and report rare upsetting experiences. They also perceive requesters on MTurk as fairer and more honest than employers outside of the platform.[181]

When Facebook began its localization program in 2008, it received criticism for using free labor in crowdsourcing the translation of site guidelines.[214]

Typically, no written contracts, nondisclosure agreements, or employee agreements are made with crowdworkers. For users of the Amazon Mechanical Turk, this means that employers decide whether users' work is acceptable and reserve the right to withhold pay if it does not meet their standards.[226] Critics say that crowdsourcing arrangements exploit individuals in the crowd, and a call has been made for crowds to organize for their labor rights.[227][188][228]

Collaboration between crowd members can also be difficult or even discouraged, especially in the context of competitive crowd sourcing. Crowdsourcing site InnoCentive allows organizations to solicit solutions to scientific and technological problems; only 10.6% of respondents reported working in a team on their submission.[185] Amazon Mechanical Turk workers collaborated with academics to create a platform, WeAreDynamo.org, that allows them to organize and create campaigns to better their work situation, but the site is no longer running.[229] Another platform run by Amazon Mechanical Turk workers and academics, Turkopticon, continues to operate and provides worker reviews on Amazon Mechanical Turk employers.[230]

America Online settled the case Hallissey et al. v. America Online, Inc. for $15 million in 2009, after unpaid moderators sued to be paid the minimum wage as employees under the U.S. Fair Labor Standards Act.

Other concerns

Besides insufficient compensation and other labor-related disputes, there have also been concerns regarding privacy violations, the hiring of vulnerable groups, breaches of anonymity, psychological damage including PTSD, the encouragement of addictive behaviors, and more. Many but not all of the issues related to crowdworkes overlap with concerns related to content moderators.

Neurophilosophy

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