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The following article was written by Scott A. Snyder, a senior fellow at Wharton, adjunct professor at Penn Engineering, and chief digital officer at EVERSANA; and Hamilton Mann, group vice president, digital marketing and digital transformation at Thales.

In recent months, the rapid adoption of generative artificial intelligence (Gen AI), exemplified by OpenAIs software ChatGPT, has propelled AI into the global spotlight. However, amidst the fascination with the new super-human capabilities offered by AI, there is an emerging algorithmic divide fueled by both disparities in technology access and literacy, along with cognitive biases inherent in AI models trained on available data. Bringing these challenges to the forefront will allow us to openly manage them across industry, creators, and society.

While the ubiquity of AI in our lives is evident, it is important to acknowledge that its impact is not uniform across the globe. Beyond the well-known digital divide, the development and proliferation of AI have given rise to an algorithmic divide. This divide separates regions where AI thrives from those where it remains largely unexplored. Brookings Mark Muro and Sifan Liu estimate that just 15 cities account for two-thirds of the AI assets and capabilities in the United States (San Francisco and San Jose alone account for about one-quarter). As humans increasingly interact with algorithms, we are bound to undergo adaptations that could reshape our thinking, societal norms, and rules. And while new AI technologies such as large language models are poised to disrupt white-collar jobs maybe even more so than blue-collar jobs, professionals from underserved communities face a major gap in access to broadband and computing technologies that are vital to upskilling ahead of this shift. The algorithmic divide needs to be front and center for business and political leaders as we navigate this new wave of AI-driven transformation so this disparity does not get worse.

As AI becomes an integral part of our lives, its imperative to examine the ethical and responsible principles associated with its presence in society. While the focus often rests on biases transmitted from humans to machines, it is essential to recognize the vast array of biases ingrained in human cognition. These biases extend far beyond our individual or collective awareness and include confirmation bias, survivor bias, availability bias, and many others. Acknowledging these biases is crucial because attempting to eliminate them from the intelligent systems we develop is an unattainable goal for humanity. Just as data privacy has become more of a universal right for citizens, proposed legislation like the European Unions AI Act and The Algorithmic Accountability Act in the U.S. are attempting to add transparency and protect consumers against AI bias.

Eliminating one bias often introduces another. The impact of AI on human existence becomes a paramount concern, surpassing the issue of biases themselves. Creators of artificially intelligent entities bear the responsibility of continuously auditing the societal changes caused by these systems and optimizing positive effects while minimizing harm. As cognitive biases can have profoundly negative consequences, their amplification through AI raises critical questions. What are the potential negative effects of artificially augmented cognitive biases when computing power acts as an amplification factor? Are companies prepared to take responsibility for the unintended consequences that AI-based agents may impose on humans as we rely more on machines to augment our decisions? Can AI aid in reducing biases in datasets, and how do we determine which biases are tolerable or dangerous?

The algorithmic divide needs to be front and center for business and political leaders as we navigate this new wave of AI-driven transformation so this disparity does not get worse.

A vital concept for AI creators to grasp is that the introduction of one AI in society inevitably gives rise to another a counterpart or alter ego. As AI advances and achieves unprecedented efficiency, a complementary AI emerges to restore equilibrium. This Dual-Sided Artificial Intelligence (DSAI) effect ushers in an era of machine-to-machine interaction and competition. It is crucial for AI creators to ensure that human agency remains central in this landscape. The defects and qualities of AI, which derive from their human creators, present a superhuman challenge due to the often-invisible biases inherent in these systems. OpenAI has developed its own classifier to allow users to understand if a written response was generated by a human or AI and also the ability to reference where the underlying data was sourced from.

As the new wave of AI technologies propels us towards a new paradigm for work and life with both promise and peril ahead, what can leaders do now to head off the looming algorithmic divide that will grow if left unchecked?

The algorithmic era, already unfolding in various parts of the world, necessitates contemplation of humanitys role in the face of AI-driven machine-to-machine interactions. Developing responsible practices that prioritize humans is not merely a competitive advantage or a localized endeavor. It is not a competitive advantage that would be the exclusive property of any specific company. Any other practice could not, and should not, be contemplated.

Just like any other disruptive tech wave like the internet, it will be critical for society to guide the evolution of generative AI in a direction where the benefits are available to the full spectrum of innovators and end-users who want to leverage this powerful technology, especially those with the least access today.

Elon Musk, Steve Wozniak, and notable scientists are asking for a break on the development of artificial intelligence superior to version 4 of ChatGPT. Now is the time for leaders to define the fundamental and universal principles to guide their organizations use of powerful AI technologies in the future, to ensure we shape an ethical AI landscape that serves humanitys best interests.

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The Looming Algorithmic Divide: Navigating the Ethics of AI - Knowledge@Wharton