Honeybee democracy in ancient Athens
Do we need more human swarm problem solving to solve societal challenges today?
The crowd jury in ancient Athens
The People´s Court in ancient Athens was an astonishing invention. In the classical period, the jurors met approximately 200 days a year. The Court tried both civil and penal cases, and also controlled other political institutions buy organizing prosecutions against public officials. The system was dependent on the voluntary efforts of citizens at large. Citizens had to “present their case” without any lawyers and there was no public prosecutor who brought a charge. In several ways, the system was organized according to principles from studies of wisdom of the crowd (Surowiecki, 2005).
"The book “Cultural-historical perspectives on collective intelligence” argues that human swarm problem solving is a type of collective problem solving that is qualitatively different from collaborative problem solving. It aims to utilize more human diversity by involving a larger group of contributors."
Rolf K. Baltzersen, Professor Østfold University College and OsloMet
The large crowd jury
On a normal court day, 1500-2000 jurors were selected by lot. It varied whether the day was devoted to smaller private suits with 201 jurors or larger ones with 401, or to public prosecutions with 501 or more. The most important political cases could include panels of 1001, 1501, 2001, and 2501. The size of the jury followed the seriousness of the case, suggesting that the Athenians had some awareness of a wisdom of the crowd-effect. By increasing the size of the jury, it was assumed that this also increased the likelihood of reaching an accurate and fair decision (Hansen, 1991). The citizens were selected according to complex randomized procedures that guaranteed that jury panels were broadly representative of the Athenian population as a whole. Any citizen could also become member of the ‘People’s Court’, including the poorer members of society. The main purpose was to optimize a good rotation among the jurors and to stop any attempts to bribe jurors. Because so many of the citizens were jurors, there must have been a strong sense of civic awareness and feeling of inclusion in the society.
To minimize the risk of corruption, the court meeting followed specific procedures. Jurors were not allowed to discuss the cases with each other during the court meeting, Since the courts were also set on the same day and decisions were made the same day, it was very difficult to bribe the jurors. Decision speed was essential as all trials finished within one day. A public prosecution would normally last nine and a half hours. The accuser and the accused had about three hours for their speech. The remaining three hours were needed to select jurors, read the charge, vote, and arrange new speeches for meting out of punishment, a further vote on the punishment, and so forth. Private suites would normally last from one to two hours. Trial outcomes were reached at incredible speed increasing the risk of jurors making the wrong decision.
However, one could argue these rapid decisions were compensated by increasing the jury group size, which was much larger than a normal jury size today. The tradeoff between making rapid and accurate decisions is addressed by using a very large crowd of jurors. Even the smallest group of 201 jurors is large enough to likely benefit from the law of large numbers.
Independent individual opinion-making
The jurors also had to swear the Heliastic Oath: I will cast my vote in consonance with the laws and with the decrees passed by the Assembly and by the Council, but, if there is not law, in consonance with my sense of what is most just, without favor or enmity. I will vote only on the matters raised in the charge, and I will listen impartially to accusers and defenders alike (Hansen, 1991: 182).
Both the emphasis on individual assessment of what is “most just” and the ability to “listen impartially” resembles the original focus on independent opinions as a basic characteristic in a wisdom of crowd - approach. The phrase “without favor or enmity” in the oath also shows how social influence is perceived as a potentially negative factor. Because jurors were selected every day, new people would sit together every day, which made it difficult to establish informal subgroups. To ensure independent opinion-making, there was a vote by secret ballot, not by hand like in the Assembly. Because voting was anonymous, the oath might seem like an empty formality, but jurors feared divine punishment. Therefore, a decision made by sworn jurors was considered more important than decisions in the Assembly where participants did not swear any oath (Hansen, 1991: 183).
Compared to court trials today, these procedures are much shorter and one can reasonably ask if they are too short when there is no time for juror deliberation. In the legendary trial against Socrates in ancient Athens, scholars have claimed that he invited his own death by first joking and arguing he should be rewarded and not punished. In the trial, there were two rounds of voting. When Socrates was first found guilty, the two involved parties proposed one penalty each and both parties held a short new speech where they argued for the proposed penalty. The jurors were required to select one of these two options. This system made the penalty decision very time efficient. However, if the defender wanted to win a majority vote, he would have to propose a reasonable penalty that could stand a chance of winning the vote. Eventually, Socrates proposed a very small fine and was found guilty by a vote of 280 to 220, which indicates that he probably would have avoided the death penalty if he had not joked and proposed a higher fine.
Most citizens must still have acknowledged the jury system as a legitimate decision-making method as even Socrates accepted his verdict, claiming, “He owed it to the city under whose laws he had been raised to honor those laws to the letter.” (“Socrates was guilty as charged,” 2009)
From a collective intelligence perspective, the jury system is strikingly similar to what characterizes a wise crowd (Surowiecki, 2005). Quality decisions were ensured through large group size, representative jury panels, majority voting with binary options, and independent judgements. Large groups increase the probability of reaching a correct verdict when individual opinions were unbiased. In addition, the lottocratic selection of jurors ensured a randomized representation of the Athenian community.
What is remarkable, is that some animals also utilize similar crowd wisdom-principles when they make decisions. The honeybees are no exception when they need to find a new home. Their survival depends on this decision, and this is why they use a lot of effort in searching for possible home sites and debate it for several days. What is remarkable, is that the bees almost always select the single best site in their surroundings. About two thirds of the bees, a group of ten thousand bees, leave together to create a daughter colony. The migrants travel only about 30 meters before they stop and form a beardlike cluster, where it is vital they make an optimal decision within just a few days.
Several hundred scout bees travel out and explore 70 square kilometers (30 square miles) of the surrounding landscape for potential home sites. None of the bees checks the same area, they are able to maximize the diversity of their searching behavior. Within just a day, they will often be able to identify all the available options, typically a dozen potential home sites within just hours. (Seeley, 2010). This is possible because the scouts meet at the cluster and freely share information about all the available options. They announce the discovery through a waggle dance which tries to recruit other scouts to fly out and evaluate the sites independently, and then return to dance for that site.
What is extraordinary with the honeybee waggle dance is that it gives specific information about the distance, direction, and desirability of the site. For instance, the number of dance circuits inform about the relative desirability of the site. The better the site is, the stronger the advertising dances will be. The dance attracts the other uncommitted scout bees to a specific site. At any given point of time, some scout bees will be committed to a candidate, while others are still uncommitted. A committed scout will advertise “her” site to uncommitted scouts and recruit them to visit the advertised site. When the recruited bees return, they advertise the same site and begin to recruit even more scouts to the particular site. Dances are more frequent for better sites, leading to a faster recruitment of scouts. This is how the positive feedback loop of recruitment to the different sites begins. The bees that have found the best site will gain supporters more rapidly and these supporters will move back to a neutral status more slowly. The interest in some sites will shoot up, while others fade away. Supporters of one site can also become apathetic and rejoin the neutral voters (Seeley, 2010).
All bees are free to advocate any site and it is also important that they do a personal independent evaluation of the different sites. Each individual decides whether she want to fly out to the site and whether she want to advertise it when returning. No scout bee will follow another dancer without inspecting the site. If scout bees were to blindly copy other bees, they would make biased decisions by overemphasizing the reports from the first scouts.
The positive feedback mechanisms aim to recruit a sufficient number of scouts to one site to pick a winner. Even when the best site is discovered several hours after the other candidates, it will still quickly dominate the competition. When the scouts visiting one of the potential home sites exceed a specific threshold number, a quorum response is initiated which suddenly makes them return to the swarm. There is enough evidence to make the best decision. Back in the swarm, the scout bees who are convinced inform the other bees to begin warming their flight muscles through piping signals. These preparations even begin before all scouts have reached consensus since it is vital to speed up the process. Quorum responses ensure that the consensus decisions are both very accurate and time (Seeley, 2010).
Do we need more human swarm problem solving to solve societal challenges today?
Today, the important question is if human swarm problem solving should be used more to solve societal challenges. One example is the use of citizens are involved in idea generation (Better Reykjavik) and how citizen assemblies are used to address difficult political issues. Deliberative Polling is another example that resemble how honeybees quickly solve problem together. This participatory governance method includes the “whole territory” by inviting a representative sample from the whole population in a region or country. Random sampling ensures inclusion by gathering the whole population in a smaller group to make it easier to deliberate. Demographic and attitudinal representativeness ensures that all relevant viewpoints and interests are included in an appropriate proportion in relation to the population. Here, the group sample needs to be large enough, involving several hundred participants to include all relevant diversity in the whole population. If all members have an equal chance to participate, this is another variant of equal opportunity (Fishkin, 2018).
The poll participants are the “scout humans” that do the work for the entire population. Similar to bee nest siting, the poll participants will typically meet to deliberate a couple of days. While the bees are genetically designed to share and listen to all information in an open way, humans will often need somebody to help them organize a similar process. Small group discussions can easily become polarized. This challenge by using balanced info materials and moderators that ensure that everyone are allowed to speak. They are trained to bring out minority opinion and to set a tone for respecting all opinions equally. In order to ensure independent opinions, and avoid conformity pressure, the participants’ final considered judgments are collected in confidential questionnaires at the end of the process (Fishkin, 2018).
An interesting example of Deliberative Polling is the participatory budgeting project in the capitol of Ulaan Baator, Mongolia. 317 persons participated two full days in the Government Palace. These respondents were drawn from a larger stratified random sample of 1,502 residents. The randomly selected individuals comprised a balanced representation of households, from both apartment areas and the traditional tent communities. When the participating residents arrived, they were randomly assigned to small groups of about fifteen persons who would be together during the weekend. The participants received briefing materials and the moderators supported the group processes. The groups also identified key questions that panels of competing experts addressed in the plenary sessions (Fishkin, 2018: 94-95).
It was expected that the final results would give the proposed Metro system top priority, but instead the best-ranked proposal was “improved heating for schools and kindergartens”, mainly because Ulaanbaatar is one of the coldest major cities in the world. The groups also opted for a cleaner environment even if it would make energy prices higher. In addition, the participants reported greater respect for others´ opinions by being part of the process. The results from the Poll were afterwards included in the Action Plan for the City Master Plan in the exact order determined by the citizens. Other elected representatives in the city also experienced the process as a legitimate democratic process. Furthermore, in 2017, the parliament of Mongolia passed a law that requires Deliberative Polling as a form of public consultation before the parliament can consider amendments to the constitution. In the first poll that built on this law, a national random sample of 785 was invited over the weekend to deliberate in the Government Palace. It was an extraordinarily high rate of participation for those invited. Also on this occasion, the results gave important advice to the national parliament. Two of the two most ambitious proposals for change, the indirect election of the president and introduction of a second chamber, were rejected. The main reason were the negative results from the Deliberative Polling (Fishkin, 2018).
The book “Cultural-historical perspectives on collective intelligence” argues that human swarm problem solving is a type of collective problem solving that is qualitatively different from collaborative problem solving. It aims to utilize more human diversity by involving a larger group of contributors. Deliberative Polling is only one such example. There are numerous other examples of swarm problem solving such as online innovation contests and crowd peer review. They are often labeled as crowdsourcing, but they all share some common characteristics. They describe a predefined problem and problem-solving procedures with a solution that needs to be identified within a short time frame. The interaction structures in the crowd varies, ranging from independent contribution to dependent contributions within both centralized and decentralized networks.
In order to solve urgent challenges in our society, the author of the book suggests that one need to better understand mechanisms behind the different types of collective problem solving.
Baltzersen, R. K. (2022). Cultural-Historical Perspectives On Collective Intelligence. Cambridge University Press. Link to Open Access version.
You can also read a news article in Norwegian related to this book "Hvordan løser vi best problemer i grupper?"
Fishkin, J. S. (2018). Democracy when the people are thinking P: Revitalizing our politics through public deliberation. Oxford, UK: Oxford University Press
Hansen, M. H. (1991). The athenian democracy in the age of demosthenes: Structure, principles, and ideologys. Oxford, UK: Blackwell
Seeley, T. D. (2010). Honeybee democracy. Princeton, NJ: Princeton University Press
Socrates was guilty as charged. (2009, June 8). University of Cambridge. News. Link.
Surowiecki, J. (2005). The wisdom of crowds: Why the many are smarter than the few. London: Abacus.