Maëlle Gavet at the WEF: “…the Australian government’s new “data-driven profiling” trial for drug testing welfare recipients, to US law enforcement’s use of facial recognition technology and the deployment of proprietary software in sentencing in many US courts … almost by stealth and with remarkably little outcry, technology is transforming the way we are policed, categorized as citizens and, perhaps one day soon, governed. We are only in the earliest stages of so-called algorithmic regulation — intelligent machines deploying big data, machine learning and artificial intelligence (AI) to regulate human behaviour and enforce laws — but it already has profound implications for the relationship between private citizens and the state….
Some may herald this as democracy rebooted. In my view it represents nothing less than a threat to democracy itself — and deep scepticism should prevail. There are five major problems with bringing algorithms into the policy arena:
- Self-reinforcing bias…
- Vulnerability to attack…
- Who’s calling the shots?…
- Are governments up to it?…
- Algorithms don’t do nuance….
All the problems notwithstanding, there’s little doubt that AI-powered government of some kind will happen. So, how can we avoid it becoming the stuff of bad science fiction? To begin with, we should leverage AI to explore positive alternatives instead of just applying it to support traditional solutions to society’s perceived problems. Rather than simply finding and sending criminals to jail faster in order to protect the public, how about using AI to figure out the effectiveness of other potential solutions? Offering young adult literacy, numeracy and other skills might well represent a far superior and more cost-effective solution to crime than more aggressive law enforcement. Moreover, AI should always be used at a population level, rather than at the individual level, in order to avoid stigmatizing people on the basis of their history, their genes and where they live. The same goes for the more subtle, yet even more pervasive data-driven targeting by prospective employers, health insurers, credit card companies and mortgage providers. While the commercial imperative for AI-powered categorization is clear, when it targets individuals it amounts to profiling with the inevitable consequence that entire sections of society are locked out of opportunity….(More)”.