Airbnb has a patent on software that analyzes social media accounts of potential guests and hosts and can supposedly flag people who show signs of “neuroticism and involvement in crimes," "narcissism, Machiavellianism, or psychopathy" or "are perceived as untrustworthy."

From Evening Standard:

It uses artificial intelligence to mark down those found to be “associated” with fake social network profiles, or those who have given any false details. The patent also suggests users are scored poorly if keywords, images or video associated with them are involved with drugs or alcohol, hate websites or organisations, or sex work.

It adds that people “involved in pornography” or who have “authored online content with negative language” will be marked down.

An Airbnb spokesperson told Business Insider that it is not using all the screening features listed in the patent.

Photo by BROTE studio from Pexels Read the rest

Princeton computer scientist Arvind Narayanan (previously) has posted slides and notes from a recent MIT talk on "How to recognize AI snake oil" in which he divides AI applications into three (nonexhaustive) categories and rates how difficult they are, and thus whether you should believe vendors who claim that their machine learning models can perform as advertised. Read the rest

Cathy "Weapons of Math Destruction" O'Neil wants us to have empathy for Big Tech CEOs like Mark Zuckerberg and Jack Dorsey, who are "monumentally screwed, because they have no idea how to tame the monsters they have created." Read the rest

In my latest podcast (MP3), I read my short story "Affordances," which was commissioned for Slate/ASU's Future Tense Fiction. it's a tale exploring my theory of "the shitty technology adoption curve," in which terrible technological ideas are first imposed on poor and powerless people, and then refined and normalized until they are spread over all the rest of us. Read the rest

"Affordances" is my new science fiction story for Slate/ASU's Future Tense project; it's a tale exploring my theory of "the shitty technology adoption curve," in which terrible technological ideas are first imposed on poor and powerless people, and then refined and normalized until they are spread over all the rest of us. Read the rest

Hirevue is an "AI" company that companies contract with to screen job applicants: it conducts an hour-long videoconference session with applicants, analyzing their facial expressions, word-choices and other factors (the company does not actually explain what these are, nor have they ever subjected their system to independent scrutiny) and makes recommendations about who should get the job. Read the rest

The idea that you can detect lies by analyzing "microexpressions" has absorbed billions in spending by police forces and security services, despite the fact that it's junk science that performs worse than a coin-toss. Read the rest

The Pentagon is seeking bids to improve its Advanced Targeting and Lethality Automated System (ATLAS) so that it can "acquire, identify, and engage targets at least 3X faster than the current manual process." Read the rest

BAE developed the London Counter Fraud Hub, which uses machine learning systems to detect benefit fraud; after trials in the boroughs of Camden, Ealing, Croydon and Islington, the system has been approved for regular use, despite an admitted 20% failure rate. Read the rest

"Predictive policing" is the idea that you can feed crime stats to a machine-learning system and it will produce a model that can predict crime. It is garbage. Read the rest

Deon is a project to create automated "ethics checklists" for data science projects; by default, running the code creates a comprehensive checklist covering data collection and storage, modeling and deployment: the checklist items aren't specific actions, they're "meant to provoke discussion among good-faith actors who take their ethical responsibilities seriously. Because of this, most of the items are framed as prompts to discuss or consider. Teams will want to document these discussions and decisions for posterity." Read the rest

Sarah Gailey's micro-short-story STET is a beautiful piece of innovative storytelling that perfectly blends the three ingredients for a perfect piece of science fiction: sharply observed technological speculation that reflects on our present moment; a narrative arc for characters we sympathize with; and a sting in the tail that will stay with you long after the story's been read. Read the rest

Some parts of machine learning are incredibly esoteric and hard to grasp, surprising even seasoned computer science pros; other parts of it are just the same problems that programmers have contended with since the earliest days of computation. The problem Amazon had with its machine-learning-based system for screening job applicants was the latter. Read the rest

Cash bail has turned American jails into debtors' prisons, where the wealthy can go about their business while awaiting trial, and the poor can languish for months or even years in jail because they can't make bail (in practice, they generally plead guilty, regardless of their innocence). Read the rest

After learning that Amazon was pushing the use of Rekognition, its facial recognition tool, for use in policing (a global phenomenon that is gaining momentum despite the material unsuitability of these tools in policing contexts), the ACLU of Northern California had a brainwave: they asked Rekognition to evaluate the faces of the 115th Congress of the United States. Read the rest

Kudos to the Gates Foundation, seriously: after spending $775m on the Intensive Partnerships for Effective Teaching, a Big Data initiative to improve education for poor and disadvantaged students, they hired outside auditors to evaluate the program's effectiveness, and published that report, even though it shows that the approach did no good on balance and arguably caused real harms to teachers and students. Read the rest

One of the more fascinating and horrible details in Reuters' thoroughly fascinating and horrible long-form report on Trump's cruel border policies is this nugget: ICE hacked the risk-assessment tool it used to decide whom to imprison so that it recommended that everyone should be detained. Read the rest