This draft paper proposes a development framework for the next generation of generative AI tools for design and manufacturing (“NextGen-AI”):

  1. Provide better information about engineering tools, repositories, search methods, and other resources to augment the creative process of design;
  2. Integrate adherence to first principles when solving engineering problems;
  3. Leverage employees’ experiential knowledge to improve training and performance;
  4. Empower workers to perform new and more-expert productive tasks, rather than pursue static automation of workers’ current functions;
  5. Create a collaborative and secure data ecosystem to train foundation models;
  6. Ensure that new tools are safe and effective.

These goals are extensive and will require broad-based buy-in from business leaders, operators, researchers, engineers, and policymakers. The authors recommend the following priorities to enable useful artificial intelligence for design and manufacturing:

  1. Improve systems integration to ethically collect real-time data;
  2. Regulate data governance to ensure equal opportunity in development and ownership;
  3. Expand the collection of worker-safety data to assess industry-wide AI usage;
  4. Include engineers and operators in the development and uptake of new tools;
  5. Focus on skills-complementary deployments to maximize productivity upside.