On the BBC’s anthology series Black Mirror, each episode explores a near-future dystopia. In each episode, a small extrapolation from current technological trends leads us into a terrifying future. The series should conjure modern-day Cassandras like Cathy O’Neil, who has made a second career out of exhorting caution against algorithmic decision-making run amok. In particular, she warns that algorithmic decision-making systems, if implemented carelessly, might increase inequality, twist incentives, and perpetrate undesirable feedback loops. For example, a predictive policing system might direct aggressive policing in poor neighborhoods, drive up arrests, depress employment, orphan children, and lead, ultimately, to more crime.
Month: November 2017
Macro-causality and social science
Consider a little science experiment we’ve all done, to find out if a switch controls a light. How many data points does it usually take to convince you? Not many! Even if you didn’t do a randomized trial yourself, and observed somebody else manipulating the switch you’d figure it out pretty quickly. This type of science is easy!
One thing that makes this easy is that you already know the right level of abstraction for the problem: what a switch is, and what a bulb is. You also have some prior knowledge, e.g. that switches typically have two states, and that it often controls things like lights. What if the data you had was actually a million variables, representing the state of every atom in the switch, or in the room?
ICML 2018 Registrations Sell Out Before Submission Deadline
In a shocking tweet, organizers of the 35th International Conference on Machine Learning (ICML 2018) announced today, through an official Twitter account, that this year’s conference has sold out. The announcement came as a surprise owing to the timing. Slated to occur in July, 2018, the conference has historically been attended by professors and graduate student authors, who attend primarily to present their research to audience of peers. With the submission deadline set for February 9th and registrations already closed, it remains unclear if and how authors of accepted papers might attend.
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