A lack of federal policy has hampered the autonomous car industry's transparency with communities where the vehicles are tested, American University professor Selika Josiah Talbott said during a virtual Axios event on Tuesday.

What she's saying: "We need guidelines. Right now, it's like the Wild West. We need bumpers in place so we don't have rogue actions testing vehicles on the roadway and possibly causing harm to the general public," Talbott said.

A Silicon Valley startup is using machine learning to create individualized fitness plans designed to reduce injury risk.

Why it matters: Musculoskeletal injuries are a major cause of lost time for both athletes and members of the military. A platform like Sparta Science that can leverage machine learning to identify weak points before an injury could result in major health care savings.

The U.S. must invest in research and development in artificial intelligence to stay ahead of China and other adversaries, argues a new paper penned by Reps. Will Hurd (R-Texas) and Robin Kelly (D-Ill.) and two research groups, shared early with Axios.

Why it matters: Reps. Hurd and Kelly, along with the Bipartisan Policy Center and the Center for a New American Security, are pushing forward a bipartisan plan at a time of high tension with China. The U.S. and China compete on 5G development, artificial intelligence and other advanced technologies.

While GPT-3 has earned ecstatic reviews from many experts for its capabilities, some critics have pointed out clear issues around bias.

Why it matters: As AI becomes more powerful and more integrated into daily life, it becomes even more important to root out the persistent problem of bias and fairness.

A new general language machine learning model is pushing the boundaries of what AI can do.

Why it matters: OpenAI's GPT-3 system can reasonably make sense of and write human language. It's still a long way from genuine artificial intelligence, but it may be looked back on as the iPhone of AI, opening the door to countless commercial applications — both benign and potentially dangerous.

CalypsoAI, a machine learning startup with its roots in the defense industry, has raised $13 million to help make government and corporate AI systems more secure and free of bias.

Why it matters: Making AI systems that are free from bias, secure and explainable are all key goals as the technology gets used for increasingly important tasks.

An AI algorithm is capable of automatically generating realistic-looking images from bits of pixels.

Why it matters: The achievement is the latest evidence that AI is increasingly able to learn from and copy the real world in ways that may eventually allow algorithms to create fictional images that are indistinguishable from reality.

A collaboration with Amazon Web Services (AWS) has helped Rhode Island survive an unprecedented torrent of unemployment claims.

Why it matters: While tech companies were well-positioned to pivot to digital-first business in the wake of the coronavirus lockdown, state governments faced paralysis. With the pandemic continuing and lockdowns potentially returning, states will need to innovate to keep their systems running.

A team of scientists has developed a technique that automatically makes written sentences more polite.

Why it matters: As the authors themselves note in the paper, it is "imperative to use the appropriate level of politeness for smooth communication in conversations." And what better to determine the appropriate level of politeness than an unfeeling machine-learning algorithm?

Researchers are calling for open and free access to U.S. court records and building an AI tool to analyze them.

Why it matters: Court records are publicly available but expensive to access and difficult to navigate. Freeing up that data — and using machine learning tools to make sense of it — would help make the justice system more just.