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By John P. Desmond, AI Trends Editor   The AI stack defined by Carnegie Mellon University is fundamental to the approach being taken by the US Army for its AI development platform efforts, according to Isaac Faber, Chief Data Scientist at the US Army AI Integration Center, speaking at the  AI World Government  event held in-person and virtually from Alexandria, Va., last week.     Isaac Faber, Chief Data Scientist, US Army AI Integration Center “If we want to move the Army from legacy systems through digital modernization, one of the biggest issues I have found is the difficulty in abstracting away the differences in applications,” he said. “The most important part of digital transformation is the middle layer, the platform that makes it easier to be on the cloud or on a local computer.” The desire is to be able to move your software platform to another platform, with the same ease with which a new smartphone carries over the user’s contacts and ...

By John P. Desmond, AI Trends Editor     Advancing trustworthy AI and machine learning to mitigate agency risk is a priority for the US Department of Energy (DOE), and identifying best practices for implementing AI at scale is a priority for the US General Services Administration (GSA).     That’s what attendees learned in two sessions at the  AI World Government  live and virtual event held in Alexandria, Va. last week.      Pamela Isom, Director of the AI and Technology Office, DOE Pamela Isom, Director of the AI and Technology Office at the DOE, who spoke on Advancing Trustworthy AI and ML Techniques for Mitigating Agency Risks, has been involved in proliferating the use of AI across the agency for several years. With an emphasis on applied AI and data science, she oversees risk mitigation policies and standards and has been involved with applying AI to save lives, fight fraud, and strengthen the cybersecurity infrastructure.  ...

By AI Trends Staff     While AI in hiring is now widely used for writing job descriptions, screening candidates, and automating interviews, it poses a risk of wide discrimination if not implemented carefully.   Keith Sonderling, Commissioner, US Equal Opportunity Commission That was the message from Keith Sonderling, Commissioner with the US Equal Opportunity Commision, speaking at the  AI World Government  event held live and virtually in Alexandria, Va., last week. Sonderling is responsible for enforcing federal laws that prohibit discrimination against job applicants because of race, color, religion, sex, national origin, age or disability.      “The thought that AI would become mainstream in HR departments was closer to science fiction two year ago, but the pandemic has accelerated the rate at which AI is being used by employers,” he said. “Virtual recruiting is now here to stay.”     It’s a busy time for HR profess...

By John P. Desmond, AI Trends Editor     More companies are successfully exploiting predictive maintenance systems that combine AI and IoT sensors to collect data that anticipates breakdowns and recommends preventive action before break or machines fail, in a demonstration of an AI use case with proven value.    This growth is reflected in optimistic market forecasts. The predictive maintenance market is sized at $6.9 billion today and is projected to grow to $28.2 billion by 2026, according to a report from  IoT Analytics  of Hamburg, Germany. The firm counts over 280 vendors offering solutions in the market today, projected to grow to over 500 by 2026.     Fernando Bruegge, Analyst, IoT Analytics, Hamburg, Germany “This research is a wake-up call to those that claim IoT is failing,” stated analyst Fernando Bruegge, author of the report, adding, “For companies that own industrial assets or sell equipment, now is the time to invest in ...

By John P. Desmond, AI Trends Editor     Engineers tend to see things in unambiguous terms, which some may call Black and White terms, such as a choice between right or wrong and good and bad. The consideration of ethics in AI is highly nuanced, with vast gray areas, making it  challenging for AI software engineers to apply it in their work.     That was a takeaway from a session on the Future of Standards and Ethical AI at the  AI World Government  conference held in-person and virtually in Alexandria, Va. this week.      An overall impression from the conference is that the discussion of AI and ethics is happening in virtually every quarter of AI in the vast enterprise of the federal government, and the consistency of points being made across all these different and independent efforts stood out.     Beth-Ann Schuelke-Leech, associate professor, engineering management, University of Windsor “We engineers often th...

By John P. Desmond, AI Trends Editor    AI is more accessible to young people in the workforce who grew up as ‘digital natives’ with Alexa and self-driving cars as part of the landscape, giving them expectations grounded in their experience of what is possible.     That idea set the foundation for a panel discussion at  AI World Government  on Mindset Needs and Skill Set Myths for AI engineering teams, held this week virtually and in-person in Alexandria, Va.     Dorothy Aronson, CIO and Chief Data Officer, National Science Foundation “People feel that AI is within their grasp because the technology is available, but the technology is ahead of our cultural maturity,” said panel member Dorothy Aronson, CIO and Chief Data Officer for the National Science Foundation. “It’s like giving a sharp object to a child. We might have access to big data, but it might not be the right thing to do,” to work with it in all cases.      Thing...

By John P. Desmond, AI Trends Editor      Two experiences of how AI developers within the federal government are pursuing AI accountability practices were outlined at the  AI World Government  event held virtually and in-person this week in Alexandria, Va.   Taka Ariga, chief data scientist and director, US Government Accountability Office Taka Ariga, chief data scientist and director at the US  Government Accountability Office,  described an AI accountability framework he uses within his agency and plans to make available to others.     And Bryce Goodman, chief strategist for AI and machine learning at the  Defense Innovation Unit  (DIU), a unit of the Department of Defense founded to help the US military make faster use of emerging commercial technologies, described work in his unit to apply principles of AI development to terminology that an engineer can apply.     Ariga, the first ...