Technology-Enabled Distruption: Implications of AI, Big Data, and Remote Work

October 1–2, 2024

Organized by the Federal Reserve Banks of Atlanta, Boston, and Richmond
Hosted by the Federal Reserve Bank of Atlanta

Technological change is a fundamental impulse that sets and keeps the market economy in motion, reshaping the ways of producing and distributing goods and services, as well as the structure of firms and industries.

The purpose of this conference series is to provide a better understanding of emerging and ongoing technology-enabled disruption and to explore its implications for the broader economy. This includes exploring how technology-enabled disruption impacts businesses, workers, and consumers along with broader impacts on the overall economy and economic inclusion.

This year's edition will feature the following sessions:

  • Session One: AI, Big Data and the Path Ahead for Productivity

    Technological advancements, particularly general-purpose technologies, serve as fundamental drivers of productivity enhancement, altering production and consumption patterns and exerting a lasting impact on economic growth. The convergence of artificial intelligence (AI) with big data is seen by many as ushering in a new technological revolution, presenting vast potential for transformative productivity improvements with a low entry barrier.

    As the new technological wave undergoes rapid evolution, especially with the ascent of generative AI, questions arise regarding how businesses will harness it to reshape production processes and organizational structures. Will AI/Big Data powered productivity gains disproportionately benefit incumbent firms or offer advantages to new entrants? What will be the impact on knowledge-workers? Reflecting on past experiences with disruptive technologies such as microcomputers and the internet, and the associated productivity puzzles, how will the tangible effects of AI/Big Data materialize in measured productivity growth?

     

  • Session Two: Technological Disruptions in Insurance and Credit Markets

    Insurance companies and credit firms heavily rely on customer analytics. Advancements in AI/Big Data technologies provide them with increased capabilities to analyze and predict customer risks and adjust pricing accordingly. While this can lead to enhanced services and efficiency gains, it also raises concerns. For instance, personalized pricing may negatively impact consumers, and imperfect algorithms may escalate systemic risks. Furthermore, there's a danger that the foundational principles of risk-sharing in these markets could be compromised, with information leading some risks to become uninsurable as they become "known" to others, resulting in adverse welfare consequences.

    The emergence of these new technologies raises critical questions: How will AI/Big Data alter practices in insurance and credit markets? What impact will it have on risk sharing and credit provision? What implications does it carry for service equality? How should we assess the effects on efficiency and consumer well-being as well as financial stability? What policy and regulatory measures might help address emerging challenges?

     

  • Session Three: Shifts in How Work Gets Done: Remote work, Outsourcing, and Future Technological Disruption

    Technology enables rapid shifts in the economy that impact firms along multiple dimensions regarding to the way they operate. The arrival of the pandemic dramatically accelerated shifts toward remote work, but the longer-run impact of increases in remote work is unclear. How has the expansion of remote work over the past three years impacted the productivity of workers? How has the expansion of remote work impacted the culture and productivity of firms?

    Prior to the pandemic, firms had outsourced many jobs that in the past had once been on firm payrolls. Will the expansion of remote work lead to an increase in outsourcing and offshoring for a new set of jobs going forward? How will firms assess the scope of work for their employees as they organize their businesses? Will there be an increasing shift toward contractors? How will firms in the future be structured with respect to location and geography? And given these rapid shifts, how does uncertainty emanating from advances in technology impact the decision making of businesses as they seek to make long-term planning decisions for their firms?