| TLDR: point-and-click and closed-source software makes science hard to | reproduce.
Or consider big data and deep learning. Even if Moore's Law remains forever valid, there will never be enough computing hence data driven algorithms must favor efficiency above all else, yet the more efficient the algorithm, the less interrogatable it is,[MO] that is to say that the more optimized the algorithm is, the harder it is to know what the algorithm is really doing. That was the exact theme of a workshop held by Morgan Stanley and the Santa Fe Institute last fall titled, "Are Optimality and Efficiency the Enemies of Robustness and Resilience?"[SFI] (Every speaker's answer was some form of "yes.") And there is a feedback loop here: The more desirable some particular automation is judged to be, the more data it is given. The more data it is given, the more its data utilization efficiency matters. The more its data utilization efficiency matters, the more its algorithms will evolve to opaque operation. Above some threshold of dependence on such an algorithm in practice, there can be no going back. As such, preserving algorithm interrogatability despite efficiency-seeking, self-driven evolution is the research grade problem that is now on the table. If science does not pick this up, then Larry Lessig's characterization of code as law[LL] is fulfilled. A couple of law professors have seized on that very idea and suggested that price-fixing collusion amongst robot traders will be harder to detect than collusion amongst people[WRC]. An anti-trust DoJ litigator I know agreed with their suggestion. --dan [MO] Michael Osborne, Oxford University, personal communication, 2015 [SFI] "Optimality vs. Fragility: Are Optimality and Efficiency the Enemies of Robustness and Resilience?", 2014 www.santafe.edu/gevent/detail/business-network/1665 [LL] Lawrence Lessig, _Code: And Other Laws of Cyberspace_, Basic Books, 2000 [WRC] "When Robots Collude" (algorithms can learn to do so), 2015 uk.businessinsider.com/robots-colluding-to-manipulate-markets-2015-4 # distributed via <nettime>: no commercial use without permission # <nettime> is a moderated mailing list for net criticism, # collaborative text filtering and cultural politics of the nets # more info: http://mx.kein.org/mailman/listinfo/nettime-l # archive: http://www.nettime.org contact: nett...@kein.org
