Research & Insights

By David Rand, January 26, 2010

Altruism on Amazon Mechanical Turk


Many workers on Amazon Mechanical Turk are willing to help others at a cost to themselves, just like participants in laboratory experiments.

While traditional economic models assume that people are entirely selfish, a central theme in behavioral economics is the existence of ‘social preferences’, or caring for others. Countless laboratory experiments have demonstrated that many people are willing to help others, even at a cost to themselves. This behavior is clearly inconsistent with being motivated only by your own monetary payoff – if you are entirely selfish, you would never pay money to help someone else in the totally anonymous conditions of the lab. In this post I describe an experiment I conducted together with John Horton, and with invaluable technical assistance from Xiaoqi Zhu, that replicates the existence of social preferences on Amazon Mechanical Turk (AMT), showing that many Turkers behave altruistically.

We also demonstrate the principle of priming, another focus of great interest in experimental economics. In priming studies, stimuli unrelated to the decision task (and which do not affect the monetary outcomes) can nonetheless significantly alter subjects’ behavior.

To assess altruistic behavior on AMT, 194 subjects played an incentivized Prisoner’s Dilemma (PD), the canonical game for studying altruistic cooperation. Subjects were informed that they had been randomly assigned to interact with another Turker, and that they would each have a choice between two options, A or B. In addition to a 20 cent “show-up fee”, they were informed of the following payoff structure: if both subjects chose A, they receive each earn a 120 cent bonus; if both chose B, they would each receive an 80 cent bonus; if one chose A while the other chose B, the A player would receive 40 cents while the B player would receive 160 cents. The resulting payoff matrix is as follows (in each cell I first show the row player’s payoff, and then the column player’s payoff):










Thus A represents cooperation, and B represents defection. If both people chose A, they both do better than if both choose B. However, regardless of the other’s action, you earn more by choosing B (hence the ‘dilemma’). Rational self-interested players should therefore always select B, and it is altruistic to choose A (helping the other at a cost to you). Given previous evidence from experiments in the laboratory, however, we predicted that AMT subjects would demonstrate a level of cooperation significantly greater than 0 in a one-shot PD.

To explore the effects of priming on AMT subjects, we built on a previous study demonstrating that exposure to religious words and phrases increases altruistic behavior, particularly among those who believe in god (Shariff & Norenzayan 2007). Among the 194 subjects in our experiment, the prime group (N=89) read a Christian religious passage about the importance of charity (Mark 12:21-22) before playing the PD, whereas the no-prime group (N=105) did not. Following the PD, subjects completed a demographic questionnaire reporting age, gender, and education, and indicated whether they had ever had an experience which convinced them of the existence of god.Based on the results of Sheriff & Norenzayan, we hypothesized that the religious prime would increase cooperation, and further hypothesized that the effect would be driven by subjects that believe in god.

Consistent with our first prediction, we observe a level of cooperation significantly greater than 0 in both the no-prime (54% C: sign-rank test, p<0.001) and prime (71% C: sign-rank test, p<0.001) conditions. Consistent with our second prediction, we observe significantly more cooperation in the prime condition compared to the no-prime condition (Chi2 test, p=0.018). Consistent with our third prediction, the prime only increases cooperation among subjects who believe in god (Chi2 test, non-believers: p=0.82, believers: p=0.004). The results are visualized in Figure 1. Using logistic regression with robust standard errors, we also find that these results are robust to controlling for age, gender, country of residence (US vs non-US), religion (Christian vs non-Christian) and education.

Figure 1 Figure 1. Reading a religious passage significantly increases Prisoner’s Dilemma cooperation among those who believe in god, but not among non-believers.

To summarize, we have demonstrated two aspects of Turker behavior:

1. A majority of Turkers chose the altruistic option of cooperating in a Prisoner’s Dilemma. Thus even in the entirely anonymous and profit-motivated online labor market of AMT, many people still choose to help each other. This sort of altruistic cooperation is a fundamental part of the natural world, and is the building block of human societies. For more, see (Nowak 2006).

2. Reading a religious passage about the important of charity makes religious Turkers more altruistic, but has no effect on Turkers who do not believe in god. This shows that Turkers respond in basically the same way as “normal” lab subjects, and is fairly intuitive. Those who believe in god are receptive to calls for generosity phrased in religious language, while non-believers aren’t. Secular primes have been shown to work for both religious and non-religious subjects (Shariff & Norenzayan 2007).

Although AMT workers are certainly not a generally representative sample, this study demonstrates that they show several of the same basic behavioral features observed in behavioral laboratory experiments. Furthermore, AMT allowed this study to be run extremely quickly and inexpensively. The 200 subjects were recruited in less than 2 days, at a total cost of $253. As a behavioral researcher, this is amazingly exciting! I usually spend months and thousands of dollars per study. AMT opens the possibility of exploring countless interesting ideas that otherwise we would have had neither the time nor money to pursue.

For other studies about cooperation, reward and punishment that I’ve conducted at Harvard, see the pdfs on my webpage: