AI tutors have real impact in skills training

In the just published, and excellent, ‘PREPARING FOR THE FUTURE

OF ARTIFICIAL INTELLIGENCE OF ARTIFICIAL INTELLIGENCE’ by the White House, AI in education gets a good airing.

Darpa has an “Education Dominance” program that focuses on accelerating training from years to months. In shifting trainees from novice to expert by modelling that shift and allowing AI to use those models, they have had success in one domain IT Administrators.

The AI tutor learns from data provided by real experts and delivers one-to-one expertise in an intensive 16-week course. We are now in a position, I feel, especially with content creation, to capture expertise and deliver it on scale. This is something I’ve been doing with WildFire in large corporates.

The AI tutored learners “frequently outperform Navy experts with 7-10 years of experience in both written tests of knowledge and real-world problem solving” what the actual evaluation said was by “a wide margin”. Seems good to me.

The important point is that this general approach can be used for many other skills. Why we are not taking this approach with the massive push on apprenticeships in the UK is beyond me. My one effort at getting AI into a major skills-based organisation was met with stubborn old-school resistance.

We need radical approaches like this if we are to train people quickly for jobs that emerge in the new economy. It is no longer acceptable to regard ‘years’ as the unit of currency in education and training.

Education a slow learner

This is bold and as the separate Department of Education report referenced in the White House report says, “Performance improvement in education has lagged behind other sectors…. because of limited R&D investment, the benefits of the IT revolution have largely passed education by.”

It was good to see that the report had two major recommendations on the use of AI in learning.

Recommendations

Recommendation 3: The Federal Government should explore ways to improve the capacity of key agencies to apply AI to their missions. For example, Federal agencies should explore the potential to create DARPA-like organizations to support high-risk, high-reward AI research and its application, much as the Department of Education has done through its proposal to create an “ARPA-ED,” to support R&D to determine whether AI and other technologies could significantly improve student learning outcomes.

Recommendation 4: The NSTC MLAI subcommittee should develop a community of practice for AI practitioners across government. Agencies should work together to develop and share standards and best practices around the use of AI in government operations. Agencies should ensure that Federal employee training programs include relevant AI opportunities.

AI is not the only technology that should be considered for skills training. VR is another. With its absolute attention, emotional impact, ability to learn by doing, context and transfer, it’s a natural candidate for practical skills, as is AR.

Conclusion

As the AI revolution bites, it will (already has) have a massive effect on employment. The need to use AI in skills training is a must. If we don’t start now we will have missed a huge opportunity. Let’s use AI for human good, not be a victim of AIs success.