World Economic Forum Plays Both Sides of the AI Debate

The world’s academics, CEOs and economists convened in Davos, Switzerland, this week for the annual World Economic Forum (WEF), with artificial intelligence (AI) occupying a split place on the agenda.

On one hand, AI was portrayed as a villain that could steal elections. On the other hand, attendees presented technology applications that could improve consumer-facing applications, such as banking.

The biggest headlines focused on the negative. The event opened with a warning from the WEF that online misinformation and disinformation, generated by AI, is the top short-term risk facing countries, according to a Computer Weekly report.

With three billion people expected to vote in elections worldwide between now and 2026, the WEF ranks the risk posed by disinformation and misinformation ahead of severe weather events, social polarization and cyber security.

AI also poses new risks to computer systems if hostile states and hacking groups are allowed to automate cyberattacks, while in the longer term, dependence on AI for decision-making will create further risks, the WEF predicted in its Global Risks Report 2024.

On the flip side, several presentations illustrated practical uses for AI for improvements to banking, healthcare, workforce management and digital transformation.

One report detailed the intersection of AI and quantum computing, dubbed AQ. Led by SandboxAQ, the concept combines the ability of quantum computing to create scenarios with the data pattern recognition of AI.

The applications, according to Sandbox, do not have to wait for the arrival of true quantum computing, which still requires more development before becoming commercially available. To boil the concept down, AI is limited by access to new data, but quantum computing can create scenarios for predictive data analytics. Quantum computing principles have already been applied in the medical field for MRI analysis.

“The heart of investment lies in portfolio optimization,” stated a report delivered by Sandbox CEO Jack Hidary and HSBC CEO Colin Bell. “Quantum-inspired algorithms can help financial experts optimize diversification and asset allocation, enhancing the performance and stability of portfolios. This results in better returns and risk management for our clients.”

Portfolio management has been a big part of India’s banking industry’s use of AI, the subject of a presentation at the conference. The country’s assets under management (AUM) have increased 21% from 2022 to 2023, putting it in second place among BRIC countries. Indian banks, according to Axis Bank CEO Amitabh Chaudhry, have used AI to manage the country’s growing number of high-net worth individuals.

“Banks now have the ability to provide tailored investment and algorithmic portfolio management through enhanced usage of artificial intelligence,” Chaudhry wrote last month. “For wealthy customers, banks can use generative AI to analyze data on companies, summarize financial reports, analyze a customer’s portfolio, and make investment recommendations based on the individual’s risk appetite, financial goals, etc.

“Banks will be able to leverage AI to create portfolios for retail investors who are looking for safer investments. Hyper-personalization at an individual level, at scale, with a high level of consistency, has been made possible by AI,” he added.

Presentations also tracked the use of AI for “big idea” strategic decision-making.

More than 40% of CEOs say they use generative AI to inform their decision-making processes, according to an IBM report. According to Philip Meissner of the ESCP Business School, AI models are becoming less biased and can be effectively used for more inclusive strategic decisions.

For example, China’s Ant Financial uses artificial intelligence and data from Alipay — its core mobile-payments platform — to run a variety of businesses, including consumer lending, money market funds, wealth management, health insurance, credit-rating services, and even an online game that encourages people to reduce their carbon footprint.

“Future competitiveness may not only be about who has the most advanced AI, but also how this technology is used for strategic decision-making,” Meissner said. “A recent study found that decision-makers arrive at completely different decisions using identical AI recommendations based on their individual decision-making styles … If there is a human in the loop, we will still have to think about the psychological elements driving decision-making.”

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