Some experts have expressed concern that machine learning tools could be used to create deepfakes, or videos that take a person in an existing video and replace them with someone else's likeness. The fear is that these fakes might be used to do things like sway opinion during an election or implicate a person in a crime. Already, deepfakes have been abused to generate pornographic material of actors and defraud a major energy producer. Fortunately, efforts are underway to develop automated methods to detect deepfakes. Facebook -- along with Amazon and Microsoft, among others -- spearheaded the Deepfake Detection Challenge, which ended last June.

More and more tech companies have initiatives in place to support Diversity, Equity & Inclusion (DEI) work. But even as Chief Diversity Officers get hired and diversity statements make their way onto company websites, diverse representation in tech is still lagging. This representation deficit, particularly in product and engineering departments, has huge implications. With the current population of software engineers comprising 25% women, 7.3% Latinos and 4.7% Black people, the teams building technology are not adequately representing the people using it. Artificial Intelligence (AI) is an area of computer science that focuses on enabling computers to perform tasks that have traditionally required human intelligence.

Twitter is making changes to its photo cropping function after an investigation into racial bias in the software, the company said on Thursday. The announcement comes after users on the platform repeatedly showed that the tool -- which uses machine learning to choose which part of an image to crop based on what it thinks is the most interesting -- cuts out Black people from photos and centers on white faces instead. Tony Arcieri, a cryptography engineer, posted a series of tweets in mid-September showing how the platform's algorithm routinely chose to highlight the face of Senate Majority Leader Mitch McConnell, who is white, instead of former President Barack Obama's in multiple photos of the two. The experiment prompted others to try similar experiments with the same result, and led to the company launching an investigation into its systems shortly after. The social media company implemented its machine-learning-powered image cropping system in 2018.

Human fascination with robots has long been fused with fear. The first widespread use of the term came a century ago in a Czech play about robots manufactured to serve and work for people. The bots turn on their masters. That plot has played out in fiction countless times since. Meanwhile, the real world has created ever more advanced versions of mechanical servants.

Human fascination with robots has long been fused with fear. The first widespread use of the term came a century ago in a Czech play about robots manufactured to serve and work for people. The bots turn on their masters. That plot has played out in fiction countless times since. Meanwhile, the real world has created ever more advanced versions of mechanical servants.

It was a sunny afternoon last month when my smartphone decided to ignore me. Well, it didn't ignore my African American self, but it did ignore the carved face of a black man in a sculpture I was trying to photograph. Instead, it bracketed the carving of a white man's face to indicate that it was "seeing" him, while not bracketing the black face in the center of the frame. This problem of artificial intelligence having difficulty with black faces has been around for at least a decade. In addition to causing issues with commonplace activities, like taking pictures, it also raises a bigger question of how we guarantee equal opportunity across race in a world run on AI. AI is already ubiquitous and powerful, and it becomes more so every year.

Facial recognition technology has progressed to point where it now interprets emotions in facial expressions. This type of analysis is increasingly used in daily life. For example, companies can use facial recognition software to help with hiring decisions. Other programs scan the faces in crowds to identify threats to public safety. Unfortunately, this technology struggles to interpret the emotions of black faces.

Facial recognition technology has progressed to point where it now interprets emotions in facial expressions. This type of analysis is increasingly used in daily life. For example, companies can use facial recognition software to help with hiring decisions. Other programs scan the faces in crowds to identify threats to public safety. Unfortunately, this technology struggles to interpret the emotions of black faces.

Nissan is introducing a new fleet of autonomous robo-taxis, as part of its "Easy Ride" pilot program, starting in March. African-Americans waiting on taxis in Los Angeles are likely to face longer wait times and have a greater chance of being cancelled on than whites, Asians and Hispanics, according to a new study out Wednesday from the University of California at Los Angeles. African-Americans waiting on taxis in Los Angeles are likely to face longer wait times and have a greater chance of being cancelled on than whites, Asians and Hispanics, according to a new study out Wednesday from the University of California at Los Angeles. They also faced longer wait times and more cancellations with Lyft and Uber, which show drivers the passenger's first name -- and in Lyft's case, a name and photo -- though far less so than with taxis, according to "Ridehail Revolution: Ridehail Travel and Equity in Los Angeles," a doctoral dissertation by Anne Brown of UCLA's Institute for Transportation Studies. Taxi drivers in L.A. were 73% more likely to cancel on black riders than whites, and 25% of blacks were never sent a cab, according to the research, which had 18 UCLA students of different ethnicities hail 1,704 trips between October and December 2017.