Interesting article in the MIT Tech Review (via /.) detailing research performed at Northwestern University (paper on ArXiv) on how potentially to leverage the power of collective action in order to counter pervasive data collection strategies by internet companies. Three such methods are discussed: data strikes (refusal to use data-invasive services), data poisoning (providing false and misleading data), and conscious data contribution (to privacy-respecting competitors).

Conscious data contribution and data strikes are relatively straightforward Aventine secessions, but depend decisively on the availability of alternative services (or the acceptability of degraded performance for the mobilized users on less-than-perfect substitutes).

The effectiveness of data poisoning, on the other hand, turns on the type of surveillance one is trying to stifle (as I have argued in I labirinti). If material efficacy is at stake, it can be decisive (e.g., faulty info can make a terrorist manhunt fail). Unsurprisingly, this type of strategic disinformation has featured in the plot of many works of fiction, both featuring and not featuring AIs. But if what’s at stake is the perception of efficacy, data poisoning is only an effective counterstrategy inasmuch as it destroys the legitimacy of the decisions made on the basis of the collected data (at what point, for instance, do advertisers stop working with Google because its database is irrevocably compromised?). In some cases of AI/ML adoption, in which the offloading of responsibility and the containment of costs are the foremost goals, there already is very broad tolerance for bias (i.e., faulty training data).

Hence in general the fix is not exclusively technical: political mobilization must be activated to cash in on the contradictions these data activism interventions bring to light.