Washington, DC, is the home base of the most powerful government on earth. City agencies use automation to screen housing applicants, predict criminal recidivism, identify food assistance fraud, determine if a high schooler is likely to drop out, inform sentencing decisions for young people, and many other things. That snapshot of semiautomated urban life comes from a new report from the Electronic Privacy Information Center (EPIC). The nonprofit spent 14 months investigating the city's use of algorithms and found they were used across 20 agencies, with more than a third deployed in policing or criminal justice. For many systems, city agencies would not provide full details of how their technology worked or was used.

The recent heatwave has been tough to bear. The days are long and humid, and the nights offer little relief. I find myself cranky and short-tempered, and even the simplest tasks seem to take twice as much effort. I know I'm not alone in feeling this way - the entire city seems to be struggling under the weight of the heat. Even so, I can't help but appreciate the beauty of a summer day.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Wondering where AI regulation stands in your state? Today, the Electronic Privacy Information Center (EPIC) released The State of State AI Policy, a roundup of AI-related bills at the state and local level that were passed, introduced or failed in the 2021-2022 legislative session (EPIC gave VentureBeat permission to reprint the full roundup below). Within the past year, according to the document (which was compiled by summer clerk Caroline Kraczon), states and localities have passed or introduced bills "regulating artificial intelligence or establishing commissions or task forces to seek transparency about the use of AI in their state or locality."

With the rapid uptake of this technology throughout the industry, manufacturers need to develop a comprehensive strategy and understanding of how it works to implement it effectively. Winter shared some C-suite advice and tactics in an episode of The Technology Magazine Show. "I like to say that if you want to be effective with AI, you really need to change the way that you view it, and to do this the entire company - or at least those who make decisions - need to have a basic understanding of what AI is and how it works and how it can benefit their role and the company," says Winter. "And when doing this, you'll find ways to integrate AI into way more decisions than you're probably doing right now because you have to remember AI is essentially a decision-making tool; it can either automate decisions for you or augment your decision-making process." This is particularly significant for the manufacturing industry as according to Deloitte, manufacturing is estimated to generate about 1,812 petabytes (PB) of data every year, more than communications, finance, retail and several other industries.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Wondering where AI regulation stands in your state? Today, the Electronic Privacy Information Center (EPIC) released The State of State AI Policy, a roundup of AI-related bills at the state and local level that were passed, introduced or failed in the 2021-2022 legislative session. Within the past year, according to the document, states and localities have passed or introduced bills "regulating artificial intelligence or establishing commissions or task forces to seek transparency about the use of AI in their state or locality."

Legislation introduced last week would require companies to assess the impact of AI and automated systems they use to make decisions affecting people's employment, finances, housing and more. The Algorithmic Accountability Act of 2022, sponsored by Oregon Democratic Sen. Ron Wyden, would give the FTC more tech staff to oversee enforcement and let the agency publish information about the algorithmic tech that companies use. In fact, it follows an approach to AI accountability and transparency already promoted by key advisers inside the FTC. Algorithms used by social media companies are often the ones in the regulatory spotlight. However, all sorts of businesses -- from home loan providers and banks to job recruitment services -- use algorithmic systems to make automated decisions. In an effort to enable more oversight and control of technologies that make discriminatory decisions or create safety risks or other harms, the bill would require companies deploying automated systems to assess them, mitigate negative impacts and submit annual reports about those assessments to the FTC.

This is still not directly definable, although we still know of human abilities that even the the best present programs on the fastest computers have not been able to emulate, such as playing master-level go and learning science from the Internet. Basic researchers in AI should measure their work as to the extent to which it advances this goal. AI research should not be dominated by near-term applications. DARPA should recall the extent to which its applied goals were benefitted by basic research. NSF should not let itself be seduced by impatience.

Included are articles on integrated systems such as virtual humans, an intelligent textbook, and a game-based learning environment as well as technology-focused components such as student models and data mining. The winter issue will conclude with an article summarizing the contemporary and emerging challenges at the intersection of AI and education. Everyone recognizes the need to improve teacher effectiveness, to improve student engagement, and to create a twenty-first century education system that maximizes potential of every student. The challenges that must be addressed to make these improvements greatly exceed the scope of any single approach, whether it is educational technology, improved teacher training and better after school programs, and so on. In past research, AI -- with its inextricable links to cognitive science, psychology, and mathematics -- has proven a close fit for many of these challenging educational problems.

Included are articles on integrated systems such as virtual humans, an intelligent textbook, and a game-based learning environment as well as technology-focused components such as student models and data mining. This issue concludes with an article summarizing the contemporary and emerging challenges at the intersection of AI and education. Everyone recognizes the need to improve teacher effectiveness, to improve student engagement, and to create a twenty-first century education system that maximizes potential of every student. The challenges that must be addressed to make these improvements greatly exceed the scope of any single approach, whether it is educational technology, improved teacher training and better after school programs, and so on. In past research, AI -- with its inextricable links to cognitive science, psychology, and mathematics -- has proven a close fit for many of these challenging educational problems.

'm delighted to bring our readers the news of an exciting resource for AAAI members. AAAI has now completed a major initiative, begun five years ago, to develop a digital library of AAAI publications. The collection now comprises approximately 13,000 papers, including the full set of papers from the AAAI proceedings, papers from other major conferences, AAAI workshop and symposium technical reports, selected AAAI Press books, and the full contents of AI Magazine. This already-extensive collection is a growing resource, with new publications and access methods to be added over time. I encourage readers to visit it at the members' library section of the AAAI web site, www.aaai.org.