All the notes were taken directly from the source mentioned.
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Have we evolved to function better as group minds rather than as individuals?
It is not simply the brightest who have the best ideas; it is those who are best at harvesting ideas from others. It is not only the most determined who drive change; it is those who most fully engage with like-minded people. And it is not wealth or prestige that best motivates people; it is respect and help from peers.
For example, when I created the Media Lab Asia as a distributed organization across several universities in India, one of the biggest problems I encountered was that researchers at each university were isolated from one another and therefore their research was stagnant and unproductive. People working in the same field, and sometimes even at the same university, had literally never met each other because the university administrators and the funding agencies thought it was sufficient to have the researchers read each other’s papers and that they didn’t need to travel to meetings or conferences. It was only when they began to meet and spend informal time together that new ideas began to bubble up and new ways of approaching problems began to spread.
Adam Smith himself understood that it is our social fabric that guides the invisible hand of the market and not just competition alone. In his book Theory of Moral Sentiments he argued that it was human nature to exchange not only goods but also ideas, assistance, and favors out of sympathy. Furthermore, he thought that these social exchanges guided capitalism to create solutions for the good of the community.
What is Social physics
It is s a quantitative social science that describes reliable, mathematical connections between information and idea flow on the one hand and people’s behavior on the other.
Just as the goal of traditional physics is to understand how the flow of energy translates into changes in motion, social physics seeks to understand how the flow of ideas and information translates into changes in behavior—how people cooperate to discover, select, and learn strategies and coordinate their actions.
Who we actually are is more accurately determined by where we spend our time and which things we buy, not just by what we say we do.
The contrast between most cognitive science and social physics is quite important, however. Rather than focusing on individual thoughts and emotions, social physics focuses on social learning as the major driver of habits and norms.
In order to build a society that is better at avoiding market crashes, ethnic and religious violence, political stalemates, widespread corruption, and dangerous concentrations of power. The first steps are to begin setting scientific, reliable policies for growth and innovation, and to institute information and legal architectures for the protection of privacy and public transparency.
As Steve Jobs put it: Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty, because they didn’t really do it, they just saw something. It seemed obvious to them after a while. That’s because they were able to connect experiences they’ve had and synthesize new things.
The most consistently creative and insightful people are explorers. They spend an enormous amount of time seeking out new people and different ideas, without necessarily trying very hard to find the best people or best ideas. The most productive people are constantly developing and testing a new story, adding newly discovered ideas to the story and then trying it out on everyone they meet.
The main work of science, art, or leadership is the same: developing a compelling story about the world and then deciding to test it against reality. In science, stories are tested against real-world behavior; in the arts, against their ability to influence the ongoing cultural dialogue; and in management, against their success in business or government.
Star producers engage in preparatory exploration; that is, they develop dependable two-way streets to experts ahead of time, setting up a relationship that will later help the star producer complete critical tasks. First, they maintained stronger engagement with the people in their networks, so that these people responded more quickly and helpfully. Second, star performers’ networks were also more diverse.
This is just what I see when I look at the most productive people in the world: They are continually engaging with others in order to harvest new ideas, and this exploratory behavior creates better idea flow.
Mathematical models of learning in complex environments suggest that the best strategy for learning is to spend 90 percent of our efforts on exploration, i.e., finding and copying others who appear to be doing well. The remaining 10 percent should be spent on individual experimentation and thinking things through.
Average performers thought teamwork meant doing their part on the team. Star performers, however, saw things differently: They pushed everyone on the team toward joint ownership of goal setting, group commitments, work activities, schedules, and group accomplishments. That is, star performers promoted synchronized, uniform idea flow within the team by making everyone feel a part of it, and tried to reach a sufficient consensus so that everyone would willingly go along with new ideas.
Star performers became familiar with different perspectives on their work. Senior management, customers, sales, and manufacturing groups all have different views, and the combination of their ideas with those already in their work group were a major source of useful creative thinking.
Collective intelligence & Social Learning
Diversity of viewpoint and experience is an important success factor when harvesting innovative ideas.
This sort of idea pooling was popularized some years ago by James Surowiecki’s book on collective intelligence, and it is the basic intuition that motivates secret ballot voting, likes and star ratings on social media, and download counts on Web pages. However the evidence is that this idea-pooling approach only works for estimation problems as long as there is no social interaction. In other words, it assumes that all the people in the crowd will act independently. The moment social interaction occurs, however, all bets are off: people begin influencing other people,6 and that results in panics, bubbles, and fads. ***
In humans, the social learning strategy of feeding back the best current idea—that is, a constrained, artificial sort of social interaction that interleaves periods of idea harvesting with periods when experts evaluate the ideas—produces a wisdom of the crowd effect that works even for small groups.
Idea flow also depends on the mix of social learning and individual learning. For example, when people see others adopting strategies similar to their own, they often become more confident, and they are then likely to increase their investment in that particular strategy. People’s decisions are a blend of personal information and social information, and when the personal information is weak, they will tend to rely more on social information. In a situation where people are uncertain, the confidence-enhancing effect of social learning becomes larger.
The Facebook voting example suggests that information by itself is a rather weak motivator. On the other hand, both the ape troop and Bell Stars examples suggest that seeing members of our peer groups adopting a new idea provides a very strong motivation to join in and cooperate with others. Until people see that there is a rush to adopt a new behavior, most group members will be reluctant to go along.
Remember the Bell Stars: They pushed everyone on the team toward joint ownership of the group, involving everyone in goal setting, work activities, and getting credit for group accomplishments.
Some people clearly have impoverished opportunities for social learning because they have too few links to others. Others are embedded in a web of feedback loops, so that they hear only the same ideas over and over again, while most users have a middling number of opportunities for social learning.
Similarly, when there are feedback loops in the social network, then the same ideas circle around and come back again and again. But because ideas usually change slightly as they go from person to person, they may not be recognized as repetitions of the same ideas. It is easy to believe that everyone has independently arrived at similar strategies, and again become more confident than is warranted.
What did not predict their voting behavior? The views of the people they talked politics with, and the views of their friends. Just as with weight gain, it was the behavior of the surrounding peer group—the set of behavior examples that they were immersed in—that was the most powerful force in driving idea flow and shaping opinion.
Again, it is important to notice that it wasn’t just the number of direct interactions that mattered, but rather, it was the amount of exposure to other people’s statements and attitudes, both direct interactions through conversations and indirect interactions through incidental observation. Overheard comments and the observation of other people’s behavior are effective drivers of idea flow.
We all sail in a stream of ideas, ideas that are the examples and stories of the peers who surround us; exposure to this stream shapes our habits and beliefs.
In summary, people act like idea-processing machines combining individual thinking and social learning from the experiences of others. Success depends greatly on the quality of your exploration and that, in turn, relies on the diversity and independence of your information and idea sources.
Are our habits the result of our personal choices or do they come from the flow of ideas that surrounds us? We know that obesity, smoking, and other health-related behaviors are affected by social learning, and social support is known to be a key factor in an individual’s health and well-being.
As Nobel Laureate Daniel Kahneman might have put it, we can consciously reason about which flow of ideas we want to swim in, but then exposure to those ideas will work to shape our habits and beliefs subconsciously.
If somebody else has invested the effort to learn some useful behavior, then it is easier to copy them than to think it through all over again. As a simple example: If we have to use a new computer system, why read the manual if we can watch someone else who has already learned to use the system? People overwhelmingly rely on social learning and are more efficient because of it.
Intuition or Fast thinking
It surprises most people to learn that fast thinking is better than slow thinking for many tasks. Whenever a problem is complex and involves trade-offs between different goals, the association mechanisms used in fast thinking usually outperform the slower reasoning mechanisms.
Psychological studies have shown that the snap judgments of people are more altruistic and cooperative than the decisions made slowly and thoughtfully.
Our ancestors understood that our culture and the habits of our society are social contracts, and that both depend primarily upon social learning. As a result, most of our public beliefs and habits are learned by observing the attitudes, actions, and outcomes of peers, rather than by logic or argument.
There is considerable evidence in the scientific literature showing that unconscious cognition can be more effective than conscious cognition for solving complex problems. Because fast thinking uses associations rather than logic, it can make intuitive leaps more easily by finding creative analogies.
So even though today’s society tends to glorify the individual, the vast majority of our decisions are shaped by common sense, the habits and beliefs we have in common with our peers, and these common habits are shaped by interactions with other people.
Synchronization and uniformity of idea flow within a group is critical: When an overwhelming majority seem ready to adopt a new idea, this convinces even the skeptics to go along. A surprising finding is that when people are working together doing the same thing in synchrony with others—e.g., rowing together, dancing together—our bodies release endorphins, natural opiates that give a pleasant high as a reward for working together.
Business research has shown that this sort of engagement—repeated cooperative interactions among all members of the team—can improve the social welfare of the group, and also promotes the trustworthy cooperative behavior conducive for successful business partnerships.
The number of direct cooperative interactions also gives a surprisingly accurate prediction of their trust.
When people interact in small groups, the ability to punish or reward peers is very effective at promoting trusted cooperative behavior.
The number of direct interactions that people had with their buddies was an excellent predictor of how much their behavior would change.
The social physics approach to getting everyone to cooperate is to use social network incentives rather than to use individual market incentives or to provide additional information. That is, we focus on changing the connections between people rather than focusing on getting people individually to change their behavior. The logic here is clear: Since exchanges between people are of enormous value to the participants, we can leverage those exchanges to generate social pressure for change.
Social Pressure & Incentives
The social pressure that is generated is a function of the cost of any mismatch between the behavior of the individuals, the value of the relationship, and the amount of interaction. This means that the most effective network incentives should be focused on the people who have the strongest social ties and the most interaction with others.
We found that this Peer See approach, a sort of combined economic-social incentive scheme, was twice as effective as just rewarding people individually, without any social component (e.g., the standard economic incentive approach). The social pressure generated just by seeing what their buddies were doing doubled the effectiveness of the financial incentive. Similar to the social incentives in the Peer See experiment, the knowledge that our face-to-face friends had already voted generated enough social pressure that it convinced people to vote. Why mostly just face-to-face friends? Again, because social pressure depends on the strength of the social tie and the amount of interaction.
This is a social network effect: Identification with a group of people increases both trust of group members and the social pressure that the group can exert.
In companies in which people received a flurry of invitations to join the company’s digital social network, they were much more likely join and use the network than they were in response to the same number of invitations spread out over time. Who invited whom to join and use the digital social network mattered the most.
In fact, if anyone got three or more invitations to join the network within a half hour, and if those invitations were from people who were already engaged with them and their work group, then they were almost certain to join and give the digital social network a try. In contrast, even as many as twelve invitations within a half hour had relatively little effect if the invitations were from people who were not engaged with them or their work group.
Private Social Network
A rich social learning environment, made up of many examples from trusted peers, is required for people to adopt the habit of using a new social network within a company.
For instance, one could reward people for how much their coworkers use the network to transact business with them. Such an incentive generates social pressure to use the network and might kick-start the process of creating new habits around use of the network. Engagement builds culture.
Engagement requires interaction: If people are to work together efficiently, there needs to be what is called network constraint: repeated interactions between all of the members of the group. Good network constraint has been achieved can be tested by asking if the people you talk to also talk to each other.
Do the people one person talks to also talk to one another? How tightly woven and interconnected are peer networks?
The largest factor in predicting group intelligence was the equality of conversational turn taking; groups where a few people dominated the conversation were less collectively intelligent than those with a more equal distribution of conversational turn taking. The second most important factor was the social intelligence of a group’s members, as measured by their ability to read each other’s social signals. Women tend to do better at reading social signals, so groups with more women tended to do better.
Socially intelligent participants in our collective intelligence experiment may have been doing was enabling better idea flow by guiding the group toward briefer presentations of more ideas, encouraging responses, and ensuring that everyone contributed equally.
The characteristics typical of the highest-performing groups included: 1) a large number of ideas: many very short contributions rather than a few long ones; 2) dense interactions: a continuous, overlapping cycling between making contributions and very short (less than one second) responsive comments (such as good, that’s right, what? etc.) that serve to validate or invalidate the ideas and build consensus; and 3) diversity of ideas: everyone within a group contributing ideas and reactions, with similar levels of turn taking among the participants.
One exception to using these patterns of interaction as a guide is performance in times of stress. When the decision needs to be made now, there may be no time to get all the ideas out and discuss them. A second exception is when the group has a hard time working together and emotions are high; then a leader may have to play the role of facilitator and frequently intervene between contributions by others. These interventions should be as short as possible, though, to leave air time for new ideas.
Nevertheless, during the last century this sort of hierarchical crowdsourcing has been exactly the model of most corporations. Workers sit in cubicles doing independent tasks, and then their outputs are routed to anonymous others for the next stage of processing. Other anonymous workers then use checklists for quality control, and finally, a central management oversees the whole affair. This is why traditional encyclopedias were so expensive to produce, and why today most corporations are still inefficient and slow to change.
What we found was that the patterns of face-to-face engagement and exploration within corporations were often the largest factors in both productivity and creative output.
The most important factors for predicting productivity were the overall amount of interaction and the level of engagement (the extent to which everyone is in the loop).
Unfortunately, objective measures of creative output are hard to find; who can say what is truly creative? But perhaps the best available measure is the KEYS creativity assessment tools developed by Professor Teresa Amabile at Harvard.
The trick is to do what creative people do: they pay attention to any new idea that comes along, and when something is interesting, they bounce it off other people and see what their thoughts are; they also try to expand their social networks to include many different types of people, so they get as many different types of ideas as possible.
Red Balloon Challenge
That is why we rewarded people both for finding balloons and for recruiting people to help search. We rewarded people roughly equally for these two tasks, because building the network was just as important as the actual work of searching. We used a standard individual economic reward to motivate people to report balloons to us but a social network reward to get them to recruit more people.
Our Red Balloon Challenge follow-up interviews suggested that people signed up their friends as a favor to the friends. That is, recruiting a friend was like sharing a free lottery ticket. You don’t necessarily expect to win, but sharing the ticket strengthens the social ties with your friend. By sharing, you make it more likely that they will share with you or help you out on another occasion; you are building trust and social capital.
Leaders can increase its performance by promoting healthy patterns of interaction within their organizations (including both direct interactions, such as conversations, and indirect interactions, such as overhearing or observing).
Effective leaders usually have a sort of practical charisma: By being energetic and systematically engaging with others, they can help grow the interaction patterns of their organization in the right direction.
In my Harvard Business Review article The New Science of Building Great Teams I argued that moving from a management that uses org charts to a management that monitors idea flow requires a shift away from the individual talent approach to managing organizations and a move toward shaping interaction patterns to achieve better collective intelligence.
By moving away from a static org chart to a focus on the real interaction network, we can bring everyone into the loop, to make it more likely that good ideas will turn into coordinated behaviors.
Solving echo chamber problem
Bernardo Huberman’s research group at Hewlett-Packard (HP) has developed a scheme that first asks each person what they thought everyone else was going to say.
A second way was invented by Drazen Prelec at MIT, who came up with what he calls Bayesian truth serum, which is a way of figuring out who has genuinely new bits of information that might make a difference.
Third, estimate the amount of social influence between people, keep track of the dependencies between people’s ideas and their behaviors.
Organizations with such poor patterns of exploration often find themselves stuck in old patterns of behavior.
In the wise guys method, we look for individuals who can accurately predict how other people will act but whose own behavior is different. The logic is that if a person can predict other people’s actions, then they already know the common knowledge. But if their behavior is also different from everyone else’s, then they must know something the others don’t. The behavior of such wise guys, then, can be counted as an independent bit of information.
These people circulated actively through the crowd and engaged people in short, high-energy conversations, acting rather like a bee harvesting pollen. We found that the more of these charismatic connectors a given team had among its members, the better the team performance was judged during the business plan contest at the end of the week. It seems that teams whose social style is dominated by these charismatic connectors may have had more evenhanded turn taking and high levels of engagement, which is the recipe for collective intelligence.
This connection between engagement, trust, and people’s ability to act cooperatively is perhaps the main point of Robert Putnam’s classic book Bowling Alone, which highlights the relationship between civic engagement and the health of society.
City Development 1800’s
1800s, when the Industrial Revolution spurred rapid urban growth and created huge social and environmental problems. The remedy then was to build centralized networks that delivered clean water and safe food, enabled commerce, removed waste, provided energy, facilitated transportation, and offered access to centralized health care, police, and education services.
What is missing, though, are two critical items: The first is social physics, specifically dynamic models of demand and reaction that will make the system function correctly, and the second is a New Deal on Data, an architecture and legal policy that guarantees privacy, stability, and efficient government.
Perhaps surprisingly, the places we go and things we do during our free time are almost as regular as our work patterns.
Indeed, much of the language I use in this book draws from economics. But rather than study how economic agents work and how economies function, social physics seeks to understand how the flow of ideas turns into behaviors and action. Put another way, social physics is about how human behavior is driven by the exchange of ideas how people cooperate to discover, select, and learn strategies and coordinate their actions rather than how markets are driven by the exchange of money.
Finally they decide that it is time to act on it, to bring it into the light and test it against reality.
This sort of idea pooling was popularized some years ago by James Surowiecki’s book on collective intelligence, and it is the basic intuition that motivates secret ballot voting, likes and star ratings on social media, and download counts on Web pages. However the evidence is that this idea-pooling approach only works for estimation problems as long as there is no social interaction. In other words, it assumes that all the people in the crowd will act independently. The moment social interaction occurs, however, all bets are off: people begin influencing other people, and that results in panics, bubbles, and fads.
In humans, the social learning strategy of feeding back the best current idea that is, a constrained, artificial sort of social interaction that interleaves periods of idea harvesting with periods when experts evaluate the ideas produces a wisdom of the crowd effect that works even for small groups.
What does this mean for individual traders? Some people clearly have impoverished opportunities for social learning because they have too few links to others. Others are embedded in a web of feedback loops, so that they hear only the same ideas over and over again, while most users have a middling number of opportunities for social learning.
When traders had the right balance and diversity of ideas in their social network, their return on investment increases 30 percent over individual traders.
What Kelly found was that star producers engage in preparatory exploration; that is, they develop dependable two-way streets to experts ahead of time, setting up a relationship that will later help the star producer complete critical tasks.
First, they maintained stronger engagement with the people in their networks, so that these people responded more quickly and helpfully.
But what did not predict their voting behavior? The views of the people they talked politics with, and the views of their friends. Just as with weight gain, it was the behavior of the surrounding peer group the set of behavior examples that they were immersed in that was the most powerful force in driving idea flow and shaping opinion.
The star performers encouraged their work groups to behave in exactly this sort of social voting manner.
Synchronization and uniformity of idea flow within a group is critical: When an overwhelming majority seem ready to adopt a new idea, this convinces even the skeptics to go along. A surprising finding is that when people are working together doing the same thing in synchrony with others: rowing together, dancing together our bodies release endorphins, natural opiates that give a pleasant high as a reward for working together.
Similarly, business research has shown that this sort of engagement repeated cooperative interactions among all members of the team can improve the social welfare of the group, and also promotes the trustworthy cooperative behavior conducive for successful business partnerships.
We found that this Peer See approach, a sort of combined economic-social incentive scheme, was twice as effective as just rewarding people individually, without any social component (e.g., the standard economic incentive approach). The social pressure generated just by seeing what their buddies were doing doubled the effectiveness of the financial incentive.
The social physics approach to getting everyone to cooperate is to use social network incentives rather than to use individual market incentives or to provide additional information.
Similar to the social incentives in the Peer See experiment, the knowledge that our face-to-face friends had already voted generated enough social pressure that it convinced people to vote.
As with cooperation, the number of direct cooperative interactions also gives a surprisingly accurate prediction of their trust.
This ancient mechanism for combining resource discovery with group decision making is one that drives many organizations, both human and nonhuman.
Star performers became familiar with different perspectives on their work. Senior management, customers, sales, and manufacturing groups all have different views, and the combination of their ideas with those already in their work group were a major source of useful creative thinking.
There is considerable evidence in the scientific literature showing that unconscious cognition can be more effective than conscious cognition for solving complex problems.
The social physics view of organizations focuses on patterns of interaction acting as a kind of idea machine to carry out the necessary tasks of idea discovery, integration, and decision making. Leaders can increase its performance by promoting healthy patterns of interaction within their organizations (including both direct interactions, such as conversations, and indirect interactions, such as overhearing or observing).
Trust is developed by stable, frequent interactions with others, so social networks pioneer Barry Wellman
It has long been observed that physically isolated neighborhoods have worse social outcomes.
When a family had more money, they changed their balance between contact with familiar people (engagement) and unfamiliar (exploration) in order to obtain greater diversity in the people they interacted with. That is, they used their extra money to increase their exploration.
Wealth allows people to invest more in exploration. Perhaps this is because good financial status makes people feel more confident and secure in exploring new social opportunities.
The fact that cities with more exploration tend to have greater growth in their wealth suggests that harvesting new experiences and meeting new people does pay off, but it just takes a while.
What if we could have both the high levels of social engagement characteristic of traditional villages (and hence their lower crime rate), and the high levels of exploration characteristic of sophisticated business and cultural areas (and hence their greater creative output)?
What we want is the opposite: self-contained towns in which people meet each other regularly and there are many friends of friends.
Physical proximity remains perhaps the major factor in productivity and creative output.
Digital media don’t convey social signals as well as face-to-face interactions, making it harder for people to read each other, and so digital media are less useful in generating the trust needed for behavior change.
Unfortunately, today most personal data are siloed off in private companies and therefore largely unavailable.
The current best practice is a system of data sharing called trust networks. Trust networks are a combination of a computer network that keeps track of user permissions for each piece of personal data, and a legal contract that specifies both what can and can’t be done with the data, and what happens if there is a violation of the permissions. In such a system all personal data have attached labels specifying what the data can and cannot be used for. These labels are exactly matched by terms in a legal contract between all the participants stating penalties for not obeying the permission labels and giving the right to audit the use of the data. Having permissions, including the provenance of the data, allows automatic auditing of its use, and enables individuals to change their permissions and even withdraw the data.
The point here is that normal analysis methods don’t suffice to answer these sorts of questions because we don’t know all the possible alternatives and so we can’t form a limited, testable number of clear hypotheses. Instead, we need to devise new ways to test the causality of connections in the real world. We can no longer rely on laboratory experiments; we need to actually do the experiments in the real world, and usually on massive, real-time streams of data.
This model for society has its roots in eighteenth-century notions of natural law: the idea that humans are self-interested and self-commanded and that they relentlessly seek to gain from the exchange of goods, assistance, and favors in all social transactions.
Modern science now understands that cooperation is just as important and just as prevalent in human society as competition.
In fact, the main source of competition in society may not be among individuals but rather among cooperating groups of peers.
The idea of a market is a similarly flawed idealization, in this case in which it is imagined that all the participants can see and compete evenly with everyone else. In reality, some people have better connections, some people know more than others, and some purchases are more difficult than others, due to distance, timing, or other secondary considerations.
In other words, many early societies operated much more like an exchange network than a market: There was no market mechanism or price-setting authority for establishing the value of goods or ideas. Limited mobility meant that supply and demand were limited to exchanges with at most a very few people at any one time, and reputations were mostly earned one-on-one rather than shared through some central authority.
The central reason exchange networks are better than markets is trust. Relationships in an exchange network quickly become stable (we go back again and again to the person who gives us the best deal), and with stability comes trust, i.e., the expectation of a continued valuable relationship.
Adam Smith thought that the invisible hand was due to a market mechanism that was constrained by peer pressure within the community.
Our results strongly suggest that the invisible hand is more due to the trust, cooperation, and robustness properties of the person-to-person network of exchanges than it is due to any magic in the workings of the market.
Social physics suggests that the first step is to focus on the flow of ideas rather than on the flow of wealth, since the flow of ideas is the source of both cultural norms and innovation.
Social efficiency: In the language of economics, social efficiency refers to the optimal distribution of resources throughout society a process that, as Adam Smith famously described, occurs through the workings of an invisible hand. Of course, as we saw in Chapter 4, the invisible hand doesn’t work unless everyone is engaged in the same social fabric so that peer pressure can ensure that everybody will follow the same set of rules.
When such an inclusive social system is also socially efficient, this means that when one person benefits, the entire society benefits. The reverse is also implied: what harms an individual is likewise bad for society. When most people are sufficiently well off, then the measure of how well a society divides its wealth can be evaluated by the condition of its poorest and most vulnerable members. Given the well-known shortcomings of human nature, social efficiency is a desirable goal. Applying this principle to the flow of ideas within a society, we see that the exchange of ideas and information between people must reliably provide value not only to the individual but to the whole system.16 The traditional way to accomplish the goal of social efficiency has been the open market approach, that is, to provide open, public data in support of fair markets. This is a solution that has dominated our thinking for the last century. While our reliance on open data has provided transparency in many civil systems, the amount and richness of publicly available data are now leading to concerns about the end of privacy. We have discovered that simple anonymization of personal data just doesn’t work reliably, because by combining different data sets people can often be reidentified. And so we find ourselves in a situation where the guys with the biggest computers can pretty much track everything we do and where we go, creating the danger that we are moving toward a big brother society. Corporations and governments have computational capabilities far beyond what is available to individuals, and this imbalance is quickly becoming a major source of social inequality. The combination of these two trends greater data access and greater computing power produces an incredible concentration of power in the hands of government and large corporations.
When such an inclusive social system is also socially efficient, this means that when one person benefits, the entire society benefits. The reverse is also implied: what harms an individual is likewise bad for society.
This approach to sharing ideas and information relies on the strong control of personal data so that they are only ever shared as part of an agreed-to exchange, and that the data never flow any farther.
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