How institutions shaped the last major evolutionary transition to large-scale human societies.

What drove the transition from small-scale human societies centred on kinship and personal exchange, to large-scale societies comprising cooperation and division of labour among untold numbers of unrelated individuals? We propose that the unique human capacity to negotiate institutional rules that coordinate social actions was a key driver of this transition. By creating institutions, humans have been able to move from the default ‘Hobbesian’ rules of the ‘game of life’, determined by physical/environmental constraints, into self-created rules of social organization where cooperation can be individually advantageous even in large groups of unrelated individuals. Examples include rules of food sharing in hunter–gatherers, rules for the usage of irrigation systems in agriculturalists, property rights and systems for sharing reputation between mediaeval traders. Successful institutions create rules of interaction that are self-enforcing, providing direct benefits both to individuals that follow them, and to individuals that sanction rule breakers. Forming institutions requires shared intentionality, language and other cognitive abilities largely absent in other primates. We explain how cooperative breeding likely selected for these abilities early in the Homo lineage. This allowed anatomically modern humans to create institutions that transformed the self-reliance of our primate ancestors into the division of labour of large-scale human social organization.

Consequences of big data on the individual: Interview

The speed with which data has moved from being scarce, expensive and valuable, thus justifying detailed and careful verification and analysis to a situation where the streams of detailed data are almost too large to handle has caused a series of shifts to occur. Legal systems already have severe problems keeping up with, or even in touch with, the rate at which unexpected outcomes flow from information technology. The capacity to harness massive quantities of existing data has driven Big Data applications until recently. Now the data flows in real time are rising swiftly, become more invasive and offer monitoring potential that is eagerly sought by commerce and government alike. The ambiguities as to who own this often quite remarkably intrusive personal data need to be resolved – and rapidly - but are likely to encounter rising resistance from industrial and commercial bodies who see this data flow as ‘theirs’. There have been many changes in ICT that has led to stresses in the resolution of the conflicts between IP exploiters and their customers, but this one is of a different scale due to the wide potential for individual customisation of pricing, identification and the rising commercial value of integrated streams of diverse personal data. A new reconciliation between the parties involved is needed. New business models, and a shift in the current confusions over who owns what data into alignments that are in better accord with the community expectations. After all they are the customers, and the emergence of information monopolies needs to be balanced by appropriate consumer/subject rights. This will be a difficult discussion, but one that is needed to realise the great benefits to all that are clearly available if these issues can be positively resolved. The customers need to make these data flow contestable in some form. These Big data flows are only going to grow and become ever more instructive. A better balance is necessary, For the first time these changes are directly affecting governance of democracies, as the very effective micro targeting tools deployed in recent elections have shown. Yet the data gathered is not available to the subjects. This is not a survivable social model. The Private Data Commons needs our help. Businesses and governments exploit big data without regard for issues of legality, data quality, disparate data meanings, and process quality. This often results in poor decisions, with individuals bearing the greatest risk. The threats harbored by big data extend far beyond the individual, however, and call for new legal structures, business processes, and concepts such as a Private Data Commons. This Web extra is the audio part of a video in which author Marcus Wigan expands on his article "Big Data's Big Unintended Consequences" and discusses how businesses and governments exploit big data without regard for issues of legality, data quality, disparate data meanings, and process quality. This often results in poor decisions, with individuals bearing the greatest risk. The threats harbored by big data extend far beyond the individual, however, and call for new legal structures, business processes, and concepts such as a Private Data Commons.