Conclusion
If you'd asked me about the primary impediment to AI progress before I embarked on this research project, I would have said “good data”, “enough compute” or “better algorithms.” Mid-project, I'd have added organizational hurdles, energy demands outpacing utilities and local authorities’ ability to provide power, and shifting evaluation metrics.
Now? It's unequivocally education – or, more precisely, the pervasive lack of technical and scientific literacy.
This isn't solely about mastering the nuances of AI; it's a symptom of a deeper societal challenge. We see it in the fear-mongering stoked by science fiction narratives, as Astro Teller, CEO of X, astutely observes. We see it in the anxieties of parents struggling to navigate the digital landscape their children inhabit, a critical issue I encountered in a subsequent research project focused on digital Trust & Safety for kids. We see it at conferences, in the media, in our day to day conversations. Cybersecurity threats, deepfake scams, and online predators exploit our knowledge gaps.
The data paints a stark picture. Students are rapidly embracing Generative AI (with usage reported around 50%), while enterprise adoption lags significantly behind (hovering around 10% for some tools). According to Github surveys, seasoned software engineers harbor higher resistance to AI-powered coding assistants compared to those with fewer years of experience.
"Education" is an overused term. I mean competency gaps – the missing AI skills needed for an AI-first world. This naturally overlaps with corporate training initiatives. HR and Learning & Development teams must embrace evidence-based andragogy, but research suggests many are falling short, relying on outdated or ineffective methods.
And the need extends far beyond AI. A digitally fluent workforce, a technologically informed military, and critically aware parents and children are essential. Operating safely and effectively in cybersecurity, web3, and effectively protecting ourselves against deepfakes and scams requires continuous learning and a commitment to staying abreast of AI's evolving capabilities.
Moving forward, what should we do? Governments are already funding K-12 education efforts to raise digital literacy. But the 5 generations already in the workforce are getting left behind, with outdated methods like MOOCs unable to fill the void.
Speaking from the perspective of a working adult, I see two necessary components:
Internal Investment: Companies must prioritize robust upskilling and reskilling programs, not just for AI proficiency, but for broader digital literacy. This is crucial for fostering innovation, bolstering security (particularly in areas like phishing awareness), and, ultimately, enhancing employee retention.
External Investment: As AI becomes increasingly integrated into daily life, customer education becomes paramount. New roles, like Anthropic's Consumer Education Lead, highlight the need to teach people how to interact with new technology.
Ultimately, AI's future isn't solely contingent on the development of more sophisticated models. It hinges on cultivating a more AI-literate society. It requires fostering a culture of continuous learning, from the classroom to the boardroom, to not only safeguard against the inherent risks, but to unlock the full transformative potential of this powerful technology.