Group items tagged

Unintended consequences can be grouped into three types: Unexpected benefit: A positive unexpected benefit (also referred to as luck, serendipity or a windfall). Unexpected drawback: An unexpected detriment occurring in addition to the desired effect of the policy (e.g., while irrigation schemes provide people with water for agriculture, they can increase waterborne diseases that have devastating health effects, such as schistosomiasis). Perverse result: A perverse effect contrary to what was originally intended (when an intended solution makes a problem worse). This is sometimes referred to as 'backfire'.

Robert K. Merton listed five possible causes of unanticipated consequences in 1936:[13] Ignorance, making it impossible to anticipate everything, thereby leading to incomplete analysis Errors in analysis of the problem or following habits that worked in the past but may not apply to the current situation Immediate interests overriding long-term interests Basic values which may require or prohibit certain actions even if the long-term result might be unfavorable (these long-term consequences may eventually cause changes in basic values) Self-defeating prophecy, or, the fear of some consequence which drives people to find solutions before the problem occurs, thus the non-occurrence of the problem is not anticipated

Artificial intelligence may have cracked the code on certain tasks that typically require human smarts, but in order to learn, these algorithms need vast quantities of data that humans have produced. They hoover up that information, rummage around in search of commonalities and correlations, and then offer a classification or prediction (whether that lesion is cancerous, whether you’ll default on your loan) based on the patterns they detect. Yet they’re only as clever as the data they’re trained on, which means that our limitations—our biases, our blind spots, our inattention—become theirs as well.

The majority of AI systems used in commercial applications—the ones that mediate our access to services like jobs, credit, and loans— are proprietary, their algorithms and training data kept hidden from public view. That makes it exceptionally difficult for an individual to interrogate the decisions of a machine or to know when an algorithm, trained on historical examples checkered by human bias, is stacked against them. And forget about trying to prove that AI systems may be violating human rights legislation.

Data is essential to the operation of an AI system. And the more complicated the system—the more layers in the neural nets, to translate speech or identify faces or calculate the likelihood someone defaults on a loan—the more data must be collected.

So this Great Recession of ours – don’t kid yourself, it ain’t over – is a moral crisis as well as an economic catastrophe. You might even say it’s a spiritual impasse, because it makes us ask what social scaffolding other than work will permit the construction of character – or whether character itself is something we must aspire to. But that is why it’s also an intellectual opportunity: it forces us to imagine a world in which the job no longer builds our character, determines our incomes or dominates our daily lives.What would you do if you didn’t have to work to receive an income?In short, it lets us say: enough already. Fuck work.

So the impending end of work raises the most fundamental questions about what it means to be human. To begin with, what purposes could we choose if the job – economic necessity – didn’t consume most of our waking hours and creative energies? What evident yet unknown possibilities would then appear? How would human nature itself change as the ancient, aristocratic privilege of leisure becomes the birthright of human beings as such?