If someone asks a large enough number of people to guess the number of candies in a jar, the averaged answer is likely to be very close to the correct amount. True, occasionally someone may guess closer to the actual number. This might work for decision-making in decentralized job marketplaces like Aworker too. As you repeat the experiment, the same person doesn’t become better every time, the crowd is smarter than any individual. This finding is counterintuitive.
‘Collective wisdom’ can deal with three kinds of problems:
- Cognition problems: how do we get the guess right?
- Coordination problems: how do we coordinate behavior with each other knowing that everyone else is trying to do the same?
- Cooperation problems: how do we get self-interested, distrustful people to work together, even when narrow self-interest would seem to dictate that no individual should take part?
Behavioral economists and sociologists have gone beyond the anecdotic and systematically studied the issues, and have come up with surprising answers.
Why are experts not helpful?
Experts tend to be and think alike, and thus do not reflect the maximum diversity of opinions; they tend to be internally inconsistent and poor at calibrating their position — in short, they are overconfident. In a group they tend to decide by authority (groupthink), which makes dissent within the group improbable — conformity and bias rather than the challenge is the result. What’s more, subjectivity is inevitable here.
How Decentralized Ecosystems Can Benefit from ‘Collective Wisdom’
Capturing the ‘collective wisdom’ best solves cognitive problems connected with the decision-making process. There are four conditions which always apply in blockchain-based ecosystems:
- the true diversity of opinions;
- independence of opinion (so there is no correlation between them);
- decentralization of experience;
- suitable mechanisms of aggregation.
Markets are the oldest and in many ways still the best mechanism aggregation. If the market works ‘perfectly’ supply and demand match smoothly — Adam Smith’s ‘invisible hand’ has done its work better than any allocation agency ever could. Based on this insight, virtual ‘decision markets’ have been established. They work beautifully, and in most instances, they are superior to market research by experts.
Decentralized Reputation Building System called Aworker is going to become the next example of this theory successful implementation. Decentralization provides an opportunity for people to be evaluated by their skills and achievements on the job. Today interpersonal relations with an employer or first impression on the interview have a high value even it can’t show the real professional skills of a candidate (of course, it doesn’t include sales managers and public relations specialists who have to have outstanding communication and performance skills).
Aworker connects people from all around the world to make aggregate decisions without having them in one place. It is aimed to help people find a job on appropriate (to their job experience) conditions by creating a rating of the best employees in the company, city or even country. People get a chance to verify the skills of other people if they are sure that they are truly experienced in the field and get a reward for that. This is where ‘collective mind’ has an opportunity to show its wisdom and assess the real qualification of job seekers. It also creates a whole range of opportunities for companies to build honest relationships and mutual respect (more about this issue in the article ‘Why people quit their jobs?’) with a new employee and not to be forced to pay a recruitment agency for a random candidate.
In Aworker we believe in the power of ‘collective mind,’ its objectivity and wisdom which will help people with passion, relevant job experience, and proactive minds to get a new job faster, easier and get paid for the activity in the platform.