This year marks a turning point for artificial intelligence (AI). The EU parliament has voted to approve the EU AI Act after three years of negotiations, moving the conversation around responsible AI from theory to reality and setting a new global standard for AI policy.
IBM welcomed this legislation and its balanced, risk-based approach to regulating AI. Why? Because history has shown us time and again that with every new disruptive technology, we must balance that disruption with responsibility.
We’ve known for years that AI will touch every aspect of our lives and work, and there’s been much attention paid to the incredible potential of this technology to solve our most pressing problems. But not all of AI’s impact will be flashy and newsworthy–its success will also lie in the day-to-day ways that it will help humans be more productive.
The productivity and growth conundrum
Right now, technology is advancing faster than ever, but productivity is not. A recent McKinsey report shows labor productivity in the U.S. has grown at a lackluster 1.4%. The findings show that “regaining historical rates of productivity growth would add $10 trillion to U.S. GDP–a boost needed to confront workforce shortages, debt, inflation, and the energy transition.” Similar productivity slowdown is happening globally, despite the technology boom of the past 15 years.
Anthropologist Jason Hickel said “nearly every government in the world rich and poor alike, is focused single-mindedly on GDP (Gross Domestic Product) growth. This is no longer a matter of choice.”
The formula for GDP growth has historically been population growth + productivity growth + debt growth. Two-thirds of this formula, population and debt growth, are unlikely to move in the near future. Aging populations and a shrinking workforce could lead to significant talent gaps, especially in terms of highly skilled and educated workers and as skills-first training and hiring continue to ramp up. Debt access is tightening after 15 years of the lowest interest rates in modern history come to an end.
That leaves productivity gains as our main driver of GDP growth. The world needs increased productivity to drive financial success for companies, as well as economic growth for countries.
AI is the answer to the productivity problem–but only if it can be developed and deployed responsibly and with clear purpose.
Reaping the benefits on responsible AI
Gartner estimates $5 trillion in technology spending in 2024, growing to $6.5 trillion by 2026. This will be the ultimate catalyst for the next stage of growth in the global economy.
However, one in five companies surveyed for the 2023 IBM Global AI Adoption Index say they don’t yet plan to use AI across their business. Cited among their concerns: limited AI skills and expertise, too much data complexity, and ethical concerns. This is the status quo component in our current paradox. But responsibility and disruption can–and must–co-exist.
As governments focus on smart AI regulation, business leaders must focus on accelerating responsible AI adoption. I meet with clients daily–and I’ve seen four priorities emerge in the path to adoption: Model choice, governance, skills, and open AI.
Providing model choice is critical to accelerating AI adoption. Different models will be better at some tasks than they are at other tasks. The best model will depend on the industry, domain, use case, and size of model, meaning most will utilize many smaller models versus one larger model.
And with the right governance, companies can be assured that their workflows are compliant with existing and upcoming government regulations and free of bias.
In today’s economy, jobs require skills, not just degrees. Technology is evolving faster than many can follow, creating a gap between demand and skills. Leaders must now prioritize skills-first hiring and training and upskilling the existing workforce to thrive in the AI era.
Finally, leveraging open-source models and proprietary models, with well-documented data sources, is the best way to achieve the transparency needed to advance responsible AI. Open is good for diversity because it makes it much easier to identify bias, for sovereignty because all the data sources are easily identifiable, and for education because it naturally lends itself to collaboration across the community.
AI can drive a level of GDP growth that none of us have ever seen in our lifetimes. It may mean the evolution of jobs in the near term. But just as with any other technological revolution, as upskilling occurs, there will eventually be new jobs, markets, and industries.
For business and government, 2024 must be the year of adoption, where we move from the experimentation phase to the deployment phase. With the right vision and approach to responsible AI adoption, we will begin to see widespread economic benefits of this technology in the next three years, with many more years of sustained growth and prosperity to come.
Rob Thomas is SVP of Software and Chief Commercial Officer at IBM.
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