ETX Explainer: What Is Artificial General Intelligence (AGI)?
And what does it mean for entrepreneurs, investors, and brands?
Just as the tech world frenzy over the “is Sam Altman in or out or in again” at OpenAI, it’s a good time to think about what’s next for the wider artificial intelligence landscape — and what businesses, policymakers, and society at large need to know.
Events and tech in AI are moving fast. But the next phase from Large Language Models (LLMs) like ChatGPT is starting to become widely used, even if it’s not widely known yet outside of tech circles: Artificial General Intelligence (AGI).
Gartner defines AGI “as a form of AI that possesses the ability to understand, learn and apply knowledge across a wide range of tasks and domains. It can be applied to a much broader set of use cases and incorporates cognitive flexibility, adaptability and general problem-solving skills.”
Let’s break that down.
AGI is distinct from the generative AI models like ChatGPT. It refers to a form of intelligence that matches or surpasses human abilities across a broad range of tasks. Unlike specialized AIs designed for specific tasks, AGI can learn, reason, plan, and adapt across many domains, demonstrating a level of flexibility and generalization akin to human intelligence.
That word “surpasses” is something we humans (though I understand that a machine is probably reading this post too in a variety of ways) get hung up on. But haven’t we been “surpassed” by machines that have lifted turns of rock and metal beyond what any human could ever do? Don’t calculators solve complex math equations that would take the most advanced among us years to complete? Don’t programmatic systems buy and sell ad space more efficiently than any agency executive?
We’ve made peace with the vast leaps technology has made. Why does AGI frighten so many of us? Perhaps it’s because it can do some very human things at a previously unimaginable level.
“I see so many discussions where people seem to be using the term to mean different things, and that leads to all sorts of confusion,” Shane Legg, one of Google DeepMind’s co-founders, told MIT Technology Review recently. Legg is often cited as Google’s chief AGI scientist — he even came up with the term in the first place two decades ago before starting the Google-owned, UK-based AI research lab, DeepMind in 2010. “Now that AGI is becoming such an important topic—you know, even the UK prime minister is talking about it—we need to sharpen up what we mean.”
AGI can mean a lot of different things to different people and industries.
For entrepreneurs and investors, AGI presents a new level of tech that builds on the opportunities associated with gen AI. The capacity of AGI to outperform humans in economically valuable work, as shown by OpenAI, means that businesses could leverage AGI for a wide array of applications — from complex problem-solving to creative endeavors.
This versatility could lead to the birth of new markets and the transformation of existing ones. However, investments in AGI technology also come with risks and uncertainties, given its nascent stage and unpredictable trajectory.
In the case of marketing and media, which is feeling polarized by the promises and the threats to the value of creatives and analysts, AGI could revolutionize content creation, audience analysis, and personalized advertising.
Brands could use AGI to generate innovative marketing strategies, deeply understanding consumer behavior and creating content that resonates on a more personal and emotional level. However, this also raises questions about authenticity and the erosion of human creativity in advertising.
AGI's rise brings significant considerations for policymakers and society. The technology's potential to transform labor markets, redefine creativity, and reshape how we interact with machines warrants careful regulatory attention. Issues such as data privacy, ethical use of AI, and potential biases need to be addressed to prevent misuse and ensure equitable benefits.
Despite its potential, AGI faces several hurdles. Current AI models, even advanced ones like GPT-4, do not fully qualify as AGI. They showcase sparks of AGI-like capabilities but are still limited in scope. The development of AGI requires advancements not only in computational power and algorithms but also in understanding and integrating human-like attributes such as emotion, morality, and social intelligence.
The journey to AGI is a continuum. Like evaluating animal intelligence, assessing AGI involves considering multiple dimensions and contexts. This complexity suggests that AGI won't emerge suddenly but will evolve gradually, presenting incremental advancements and challenges.
For businesses, staying informed and agile is table stakes. Embracing current AI technologies while anticipating the shift towards more generalized AI capabilities will be already built into just about every industry.
For policymakers, creating flexible regulatory frameworks that can adapt to the evolving nature of AGI is essential. And for society, engaging in informed discussions about the ethical and social implications of AGI will be critical.
And that, like most crucial jobs that require critical thinking as well as a degree of empathy, is going to be up to us humans.
Note: ETX Explainers: Answers & Insights is a new content feature by By Greg Kahn and Emerging Tech Experts. Want a topic addressed? Want to contribute your thoughts or an article? Reach out.
Greg Kahn
Emerging Tech Exchange
Founder & CEO
