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The advent of Artificial Intelligence (AI) portends a potentially monumental shift in the history of human civilization, an inflection point that prompts us to ask a profound question.
Are we in the midst of a renaissance of human creativity, rich in artistic and intellectual flourishing, or will rapid advances in AI lead to a revolution that will fundamentally reshape industrial sectors, government institutions and the structural dynamics of human society?
A renaissance, derived from the French word meaning “rebirth,” is characterized by a revitalization of culture, art, and knowledge; marked by the revisitation and rethinking of classical philosophies which lead to new and profound discoveries and the adoption of new perspectives.
On the other hand, a revolution involves a more radical and potentially tumultuous and disruptive change in society. Often abrupt and marked by fundamental changes in the functioning of societies, revolutions disrupt established governmental, economic, and sociocultural frameworks to establish new norms.
The rise of AI appears to bring many benefits to healthcare, such as true precision medical care, dynamic forecasting, and advanced precision analytics. Yet how will these powerful new tools coexist with existing challenges such as medical data privacy, meaningful use regulations, and the shift to value-based care?
Traditional vs Generative AI – Gamechanger
Before determining whether AI will lead to an era of renaissance or revolution, it is essential to understand the distinctions between traditional AI and generative AI. Indeed, the latter has been made widely accessible to the general public. Traditional AI is rule-based and involves the use of algorithms programmed for specific tasks. Results are derived based on specific predefined rules and logic to solve problems. An example would be a streaming radio station recommending songs based on your previous selections.
Traditional AI systems tend to be specialized rather than generalized. They have the following characteristics:
- Limited learning scope and capacity
- Rule-based processing
- Domain-specific and specialized applications
- Transparent and explainable
What has changed today is the widespread availability of generative AI. Generative AI technology can create content including text, video, audio, images, computer code and more by processing and refining large amounts of training data and generating new original content based on similar characteristics.
Generative AI technology, on which Large Language Models (LLM) are based, is not tied to specific applications. It is generative and has the following characteristics:
- Generalization
- Variability and versatility in learning and use
- Personalization/customization
- More natural conversational skills
Expected advances in generative AI in 2024 and medical use cases
Generative AI technology continues to develop at a breakneck pace. Indeed, its rapid development trajectory is guided by few guidelines and safeguards, which partly explains why the technology is potentially so revolutionary. I expect to see six significant advances before the end of this year.
- More powerful LLMs
- Smaller language models designed to fit mobile devices
- Multimodality
- Improved reasoning
- The rise of synthetic data and improving data quality
- Personalization
These six advances have the transformative potential to chart a path toward a future of either significant revolutionary change or a renaissance that ushers in a new era of Enlightenment. Let’s take the health care field as an example. These technological advances in generative AI have the potential to revolutionize medical practices and healthcare.
From a revolutionary perspective, advanced predictive analytics, based on more powerful LLMs, higher quality data and improved reasoning, can change the speed and accuracy of personalized treatment plans. Additionally, the intersection of AI and pharmacology could potentially result in real-time analyzes of drug interactions and contraindications, thereby fundamentally changing the landscape of medical management. Continuous, real-time monitoring of treatment regimens could enable healthcare providers to anticipate and respond to side effects with unprecedented speed and accuracy.
These are revolutionary aspects in which AI can change the analytical, operational and managerial landscape to deliver quality care through the integration of AI into the fabric of our healthcare systems.
Yet, the same AI advancements mentioned above can lead to a paradigm shift in doctors' knowledge framework, where healthcare professionals become intellectually enriched in ways that inspire them to reinvent patient treatments. For example, advanced AI reasoning applied to rapid synthesis and understanding of large quantities of medical literature can provide new insights into patient care; Likewise, personalized data models can allow researchers to glean tailored treatments more suited to patients' needs. Multimodal AI systems capable of processing and interpreting a variety of data, from genetic information and imaging to behavioral factors and complex graphics, can help practitioners make more informed decisions. Such advances create cornerstones based on new knowledge, collective wisdom, and interdisciplinary collaboration within a medical community empowered by the power, speed, and fidelity of AI.
This human-informed environment is paving the way for new medical knowledge and reshaping approaches to health and wellness. Indeed, the latter potential path to human-centered holistic care keeps human professionals at the center of healthcare delivery, informed by the augmentation of AI's enormous capabilities, while the former is more revolutionary , with AI potentially taking center stage.
Which path is most likely? Are we forced to choose a path, or can we have both a renaissance and a revolution where we balance the revolutionary and disruptive aspects of AI with a renaissance of ensuring a delivery system collaborative, human-centered and ethical healthcare?
The answers to these questions often depend on how we address the challenges of a new technology and how we design and implement policies to control the progress and implementation of that technology.
Challenges and policy implications
Rapid advances in AI pose a complex set of challenges with important societal and policy implications that can determine the path forward toward an AI renaissance or revolution. One of the most important challenges is ensuring the ethical and responsible use of AI.
Alignment issues, along with concerns over privacy, security and surveillance, portend the potential for significant misuse of technology that could harm the development and delivery of healthcare. Misinformation and disinformation are spread through the use of deepfakes, and hallucinations remain a constant concern.
Indeed, never in history has a new technology presented such radically different outcomes for medicine and society as a whole. Generative AI commoditizes processing power to enable truly personalized medicine, but also carries the risk that the technology becomes more central to the mission of healthcare than what is best for the patient.
Additionally, few times in human history has technology advanced so quickly once democratized. AI development advances every month, not every year, as we have seen with other new forms of technology. In a highly democratized and accessible AI environment, how can we control the deleterious effects that can be so quickly diffused and felt throughout society?
At the same time, an AI revolution without a thoughtful policy process could have significant economic and social impacts, increasing wealth and economic inequality as job losses occur with rapid implementation of solutions cheaper and more efficient AI. As AI becomes integrated into the workplace, it could significantly displace the human workforce, leading to the disappearance of hundreds of thousands of healthcare jobs.
Currently, there are few policies in the United States to provide effective oversight and control of AI development. Additionally, the costs of using generative AI are so low that the accessibility to leveraging AI for better or worse is highly available.
As a political system, we are also unique in that the United States operates under a system of American federalism, dividing power and authority between the federal government and the 50 states. Questions related to the responsible use of AI and the degree of authority federal or state governments have to address these issues have yet to be discussed within the policy community, much less determined.
Finally, addressing policy issues solely in the context of an “American political solution,” while necessary, is not sufficient. International cooperation, guidelines and policy measures are essential to control the most harmful effects of AI on the human population, including research and healthcare delivery.
Conclusion
It is essential that we make the right choices as a society before we lose the ability to control the path AI takes. Indeed, an AI renaissance will keep humanity at the center of human success, societal progress, and holistic, healthy communities.
An AI revolution could see humans being regulated at the periphery, questioning our place and purpose in a society where digital intelligence is the primary overarching force in governing the social order, affecting our economic livelihoods , health and social.
About Robert L. Gordon III
Robert L. Gordon III is the senior strategic leader for AI and digital innovation at DSS, Inc. He is a former professor and director of American politics at the United States Military Academy at West Point, a former deputy assistant secretary at the Department of Defense, and a retired colonel. Robert is also a former White House staffer under Presidents George Bush and Bill Clinton.