Automation and technological change in USA - principal methods used by private sector employers to ease workers adaptation and reassignment of displaced employees. (1) avoiding layoff (attrition, retirement, reduction of hours of work, retraining,automation fund), (2) easing burden of unemployment (severance pay, maintenance of acquired rights, unemployment benefit), (3) facilitating employment opportunity (employment service, training programme, antidiscrimination policy). Case studies.

Automation and technological change in USA - principal methods used by private sector employers to ease workers adaptation and reassignment of displaced employees. (1) avoiding layoff (attrition, retirement, reduction of hours of work, retraining,automation fund), (2) easing burden of unemployment (severance pay, maintenance of acquired rights, unemployment benefit), (3) facilitating employment opportunity (employment service, training programme, antidiscrimination policy). Case studies.

Conference report on a meeting to examine social implications of technological change in the USA - covers aspects of automation and innovation, the impact of technological change on education and business management, uses of computers, cybernetics, etc. Conference held in columbus 1963 may 1 to 11.

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.