This Week: June 27, 2018

Reading Time: 2 minutes

Fake Photos: Fighting Fire with Fire

Adobe is investing in being able to detect fake images with machine learning.

The new research paper shows how machine learning can be used to identify three common types of image manipulation: splicing, where two parts of different images are combined; cloning, where objects within an image are copy and pasted; and removal, when an object is edited out altogether.

You Are a Search Strategy

Extremely thought-provoking piece by Carlos E. Perez on how our personalities reflect the Big5 factors of Openness, Conscientious, Extraversion, Agreeableness, Neuroticism, and how these, in turn, map to our knowledge discovery strategies.

To summarize, personality traits reflect our own discovery strategies (search algorithms) for different contexts. These contexts are environment, planning, interpersonal interaction, cooperation and introspection.

Washing Machines, Not Robot Servants

Benedict Evans makes a good argument about what machine learning really is, by focusing on automation and its application-specificity:

This gets to the heart of the most common misconception that comes up in talking about machine learning – that it is is some way a single, general purpose thing, on a path to HAL 9000, and that Google or Microsoft have each built *one*, or that Google ‘has all the data’, or that IBM has an actual thing called ‘Watson’. Really, this is always the mistake in looking at automation: with each wave of automation, we imagine we’re creating something anthropomorphic or something with general intelligence. In the 1920s and 30s we imagined steel men walking around factories holding hammers, and in the 1950s we imagined humanoid robots walking around the kitchen doing the housework. We didn’t get robot servants – we got washing machines.

Out-Debated by a Machine

This AI program could beat you in an argument—but it doesn’t know what it’s saying.

Triple Bottom Line Recall

In a rather surprising piece in the Harvard Business Review, John Elkington says it’s time for a recall on the groundbreaking concept of the “Triple Bottom Line” that he pioneered back in 1994:

Together with its subsequent variants, the TBL concept has been captured and diluted by accountants and reporting consultants. Thousands of TBL reports are now produced annually, though it is far from clear that the resulting data are being aggregated and analyzed in ways that genuinely help decision-takers and policy-makers to track, understand, and manage the systemic effects of human activity.

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