Investments in the $1 billion-range tend to grab people’s attention, so it is no surprise that the recent announcement of the Massachusetts Institute of Technology planning to open a college that will heavily emphasize Artificial Intelligence created buzz that intersected the worlds of technology and academia.
MIT intends to open the college in 2019, creating dozens of new faculty positions and offering fellowships to attract graduate students. Identifying how knowledge of AI can best be applied to various fields of study and integrated into curricula is a promising path forward in academia.
Not only is MIT’s ambitious plan revealing about how leading academic institutions view AI’s influential role in the future, but the $350 million donation by Stephen A. Schwarzman, the principal donor and CEO of the private equity firm Blackstone Group, also might be indicative of where visionary donors and investors believe their financial backing can make the most impact.
Credit MIT – with whom ISACA is a research patron – for boldly investing in preparing students for a world that will unquestionably be recalibrated by AI in the years to come.
It is important to bear in mind, though, that the existing workforce also will need to go back to school, at least in a figurative sense, when it comes to AI’s widespread emergence in the years to come. While AI will be a central force in the careers of many researchers and scholars, for most of us, AI will be more tangential – not quite at the epicenter of our roles.
This isn’t to minimize AI’s impact; to the contrary, every organization for which I consult or help lead is exploring AI or machine learning in some capacity. Enterprises are beginning to realize that if they lag on exploring how to leverage AI to drive innovation and improve customer experiences, their rivals may gain an insurmountable competitive advantage.
For most of us in information security and other technology-driven fields, AI is an exciting tool. To be able to harness that tool constructively, there is a clear need for AI-focused training and education, which is why the concept identified by MIT President L. Rafael Reif, PhD, of educating “the bilinguals of the future” – those who will be equipped to apply advanced computing aptitude to traditional fields – is a terrific objective.
Not everyone, of course, will have the good fortune to attend the type of program envisioned by MIT. Many established professionals, whose college days have long since passed, will require training and skillset refreshes to excel in their evolving roles, given the emergence of AI and other components of digital transformation.
That puts the onus on academia and industry professional associations to provide new, forward-thinking learning modalities for professionals to encourage and enable lifelong learning.
Investing in training practitioners in AI isn’t only about sparking innovation; it is also about responsibly guarding against potentially calamitous consequences of AI deployments gone wrong. ISACA’s 2018 Digital Transformation Barometer shows only 40% of global respondents are confident in their organization’s ability to assess the security of systems based on AI and machine learning, which will become increasingly problematic as organizations build AI into a growing array of products and services. The related security, privacy and ethical implications must command the attention of boards of directors and executive management.
We are beyond the tipping point when it comes to AI’s arrival, already two years past AlphaGo’s defeat of a Go grand master. As organizational leaders reflect on 2018 and refine their objectives for 2019, MIT’s plans for an AI-focused college should serve as a prominent reminder that leading organizations are recognizing the degree to which AI will impact society, and investing accordingly.
Fellow academic institutions, industry professional associations and other sources of learning and training should determine how they can provide additional resources to equip future and current practitioners with the capabilities to harness AI’s potential and mitigate related risks. Few organizations have the resources to make a splash that will rival MIT’s, but taking the opposite approach – succumbing to the inertia of the status quo – is a recipe for become obsolete in an era when embracing AI will be the only path forward.