At the recent IMF Annual Meetings in Washington, DC the Diplomatic Courier moderated two New Economy Forum discussions on the future of work, in continuation of our work advancing conversation on the subject through the Global Talent Summit, convened annually to “look at the technological, economic, socio-economic, and political dimensions of a post-employment world.”
In these “New Economy Talks”, Diplomatic Courier Chief Ana C. Rold spoke with venture capitalist Scott Hartley and Smithsonian Science Education Center Director Carol O’Donnell about how they anticipate automation will impact the landscape of early childhood education and how we cultivate new talent to address looming global challenges including infectious disease, water scarcity, energy security, and climate change.
O’Donnell spoke to the education curriculum paradigm shift that will be required to cross the chasm from the status quo to future-ready, stating that “It’s no longer good enough to give students problems to solve. We need to teach students to identify the problems that need solving.” The current teaching model that assumes a teacher to own specialized knowledge that they share with students needs to be disrupted and replaced with a more holistic and interdisciplinary approach, according to both O’Donnell and Hartley.
Even if we were successfully pacing technological development in our educational curriculum, STEM knowledge is not sufficient if students are not also able to assess complex problems and devise solutions.
Both O’Donnell and Hartley lent insight into how they think we should approach education reform to achieve these objectives. O’Donnell promoted the idea of STEM state-based “ecosystems” that identify regional stakeholders in the governmental as well as private and public sectors and engages all in the effort to sustain students’ interest in hard science. Hartley emphasized that data science is different from data literacy, and that the breaking down of disciplinary silos will be required if students are to apply different ways of thinking to technological problems.
Hartley’s experiences in Silicon Valley have taught him that “tech” is far from monolithic field—those who prosper are interdisciplinarians who excel at engaging with content from many perspectives. To support this claim, he rattled off a list of Silicon Valley A-listers whose backgrounds are all in soft sciences or humanities. He stated: “Even in this world of big data, we need smart questioners.”
It is Hartley’s hope to swing the pendulum away from fear of automation and toward hope of how it might in fact enhance human to human interface. He suggests thinking of AI as IA—intelligence augmentation. Learning to work alongside machines can make humans better by mitigating biases and providing more opportunities for connection. Data scientists will be the translators between human and machine, but humanity remains central. According to him, “the challenges we face are not strictly technical: they’re ethical, psychological and regulatory.”