A couple of weeks ago I wrote that fears that "AI will kill us" are exagerated, being fears about something that "literally ceases to exist the moment anyone pulls the plug off the computers it runs on. AI itself cannot "kill" anything more real than avatars in some simulation. AI is the most vulnerable, helpless thing ever." By pure chance, yesterday I found a post discussing exactly "why we can't just unplug it: by the time we discover it is a superintelligence it will have spread itself across many computers and built deep and hard defenses for these. That could happen for example by manipulating humans into thinking they are building defenses for a completely different reason."

Fawkes may prevent a new facial recognition system from recognizing a person but can't change or sabotage the existing systems that have already been trained on one's unprotected images. Thus, Valeriia Cherepanova and her colleagues at the University of Maryland, one of the teams at ICLR, recently addressed this issue and developed a tool called LowKey. This tool expands on Fawkes by applying perturbations to images based on a stronger adversarial attack, which can also fool the pretrained commercial models.

Ever wondered what happens to a selfie you upload on a social media site? Activists and researchers have long warned about data privacy and said that photographs uploaded on the Internet may be used to train artificial intelligence (AI) powered facial recognition tools. These AI-enabled tools (such as Clearview, AWS Rekognition, Microsoft Azure, and Face) could in turn be used by governments or other institutions to track people and even draw conclusions such as the subject's religious or political preferences. Researchers have come up with ways to dupe or spoof these AI tools from being able to recognise or even detect a selfie, using adversarial attacks – or a way to alter input data that causes a deep-learning model to make mistakes. Two of these methods were presented last week at the International Conference of Learning Representations (ICLR), a leading AI conference that was held virtually.

"I personally think that no matter which approach you use, you lose," said Emily Wenger, a Ph.D. student who helped create Fawkes. "You can have these technological solutions, but it's a cat-and-mouse game. And you can have a law, but there will always be illegal actors." Ms. Wenger thinks "a two-prong approach" is needed, where individuals have technological tools and a privacy law to protect themselves. Elizabeth Joh, a law professor at the University of California, Davis, has written about tools like Fawkes as "privacy protests," where individuals want to thwart surveillance but not for criminal reasons.

What makes the difference between a good soccer player and a great one? Players regularly train with GPS sensors strapped across their chests. Israeli sports-tech startup PlayerMaker makes a small device that tracks much more than GPS can. Worn on a player's shoes during training, its sensors and proprietary software detect every ball touch and build an accurate player "gait profile." "The sensors know if you make a pass, a run or interception," says CEO Guy Aharon.

If you're reading the tech news these days it may seems that the industry is rapidly moving toward a robot-centric dystopia lifted from a Stephen King novel. There is a reason it's called "science fiction." Not that AI, machines, and robots don't have a place in our future. Practically speaking, we are a far cry from an autonomous office or completely driverless trucking. Popular questions such as "will artificial intelligence be a massive, job-destroying shock to our economy?"

A high school junior has created a computer brain that can diagnose breast cancer with 99 percent sensitivity. Seventeen-year-old Brittany Wenger of Sarasota, Fla., wrote a breast cancer-diagnosing app based on an artificial neural network, basically a computer program whose structure is inspired by the way brain cells connect with one another. She won grand prize at the Google Science Fair for her invention in ceremony held in Palo Alto, Calif. Like other artificial intelligence programs, artificial neural networks "learn" what to do by analyzing examples they're given and they perform better if they get more examples. In addition, they're able to detect patterns in data that are too complex for human brains or other types of programs to analyze.

The global statistics for breast cancer are staggering: 1 in 8 women worldwide will be diagnosed at some point during their lifetime. Women who are diagnosed early have a 95 percent chance of living at least five years after diagnosis and it's estimated early breast cancer diagnosis could save 400,000 lives globally each year, according to the World Health Organization. Fine needle aspiration (FNA) is currently the least invasive technique to biopsy breast lumps, or masses. FNAs are less painful, less expensive to do, result in less complications for patients, and make results available more quickly than the current traditional core or open biopsies. FNAs are currently less reliable in conclusively diagnosing breast cancer than more invasive and painful techniques.

She is only 19 but has already experimented with neural networks, built prototype software to help doctors diagnose breast cancer, won a $50,000 college scholarship from Google and been invited to the White House to showcase her research. Brittany Wenger wants a dual career as a paediatric oncologist and research scientist. The teenager from Sarasota, Florida, became interested in neural networks - a form of artificial intelligence that continuously learns and mimics the human brain - in high school. She was building a neural network that could play soccer, her favourite game, when her cousin was diagnosed with breast cancer, inspiring her to put her talents to medical use. Ms Wenger came up with the idea of creating an artificial intelligence software program to analyse data from a breast tissue biopsy.

The lure of understanding biological intelligence has long occupied researchers. Success has always been measured in peer review, number of citations, or how influential some piece of work is in inspiring the next generation of re- searchers. What human-robot interaction (HRI) and artificial intelligence (AI) promises is a metric of believability that is not intrinsic to the values of the researcher or community of practice but to the utility and successful function of the robotic artifact within a larger society. This paper is a reflec- tion and response to the hypothesis that HRI is a pure, funda- mental art of artificial intelligence and the last great successor to a domain fraught with the trappings of an art that lost its way.