This draft paper proposes a development framework for the next generation of generative AI tools for design and manufacturing (“NextGen-AI”):
- Provide better information about engineering tools, repositories, search methods, and other resources to augment the creative process of design;
- Integrate adherence to first principles when solving engineering problems;
- Leverage employees’ experiential knowledge to improve training and performance;
- Empower workers to perform new and more-expert productive tasks, rather than pursue static automation of workers’ current functions;
- Create a collaborative and secure data ecosystem to train foundation models;
- 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:
- Improve systems integration to ethically collect real-time data;
- Regulate data governance to ensure equal opportunity in development and ownership;
- Expand the collection of worker-safety data to assess industry-wide AI usage;
- Include engineers and operators in the development and uptake of new tools;
- Focus on skills-complementary deployments to maximize productivity upside.