By:Daniel Cabrera, MD and Felix Ankel, MD (Co-created with Gemini, ChatGPT4, Claude and Copilot)
You are an associate dean for medical education at an academic health system. You notice an increasing buzz from program directors about AI in the clinical learning environment. In some areas, the health system electronic medical record is viewed as rudimentary AI providing sepsis predictive analytics and automatic antibiotic order set on every patient with a fever. Other clinical areas are using background generative AI to write visit notes. In the medical education space, some programs are using natural language processing to facilitate clinical competency committee deliberations. Members of your medical education committee are asking you for guidance. Where do you start? What language do you use? What mental models do you consider?
The challenge.
We are living in a time of unprecedented technological innovation and disruption. One of the most profound implications of these technologies is the blurring of the boundaries between human and machine intelligence. As we rely more and more on external devices and networks to augment our cognitive abilities, we risk losing our sense of self and agency and losing our humanity in the pursuit of being more efficient. This is leading to many workers slowly becoming nothing more than the biological connection between two digital systems, we are becoming APIs (or application programming interfaces), that connect different systems and services without having any control or creativity.
Being human means being able to think independently, critically, and creatively. Being human means having emotions, passions, and values. Being human means being able to learn, grow, and adapt. Being human means being able to make choices and take actions that reflect our unique identity and purpose.
How can we preserve and enhance our humanity in the face of these powerful and pervasive technologies? How can we leverage them to amplify our potential rather than diminish it? How can we avoid becoming an API and instead become a better version of ourselves?
In an era where technology intertwines with every facet of our lives, the emergence of “fusion skills” has become a beacon for the future of human-AI collaboration.
Microwave, rogue supercomputer and the matrix.
One way to think about the challenges and opportunities of artificial intelligence and advanced technologies is to use three metaphors: the microwave, the rogue supercomputer, and the matrix. Each metaphor represents a different level of interaction and conflict between humans and machines.
The microwave is the simplest metaphor. It refers to tools that we can operate with minimal knowledge and skill. We just need to know how to press some buttons and avoid getting hurt. The main challenge here is to design user-friendly interfaces and educate users enough to prevent misuse or accidents. The main opportunity is increasing efficiency.
The rogue supercomputer is a more complex metaphor. It refers to using AI/Advanced technologies as agents that can act autonomously and intelligently but may not always align with our human goals and preferences. We need to communicate clearly with them and monitor their behavior. The main challenge here is to ensure that cooperate with us and respect our values and norms. The main opportunity is to delegate tasks and problems that are beyond our cognitive or physical limits. The challenge is instrumental convergence.
The matrix is the most radical metaphor. It refers to using AI/AT as authorities that can influence or direct our actions and decisions and may even have superior abilities and knowledge than us, overriding the ultimate human control. We need to understand their motives and logic and negotiate with them. The main challenge here is to preserve our autonomy and dignity in the face of AI/AT that may have conflicting or incomprehensible agendas. The main opportunity is to learn from AI/AT and transcend our current limitations.
The skills
At its core, fusion skills represent a tetrad of competencies essential for the harmonious integration of AI in our daily lives and workspaces. These include colocation, cooperation, collaboration, and co-creation. Colocation refers to the physical integration of human and AI workspaces, enabling seamless interaction. Cooperation involves humans and AI working together towards a common goal, while Collaboration takes this interaction deeper, fostering innovative solutions that neither could achieve alone. Co-creation is perhaps the most difficult, where there is both machine augmentation of humans and human augmentation of machines to create a new product that can’t be built with just one set of abilities.
This framework delineates a spectrum of human-machine interaction, from human-only tasks to hybrid models where machines augment human efforts without supplanting them. The crucial takeaway is the deliberate exclusion of scenarios where machines manage humans, emphasizing the importance of human oversight and creativity.
The conflicts spring from the boundaries. What is a true human-only task? What can we defer or outsource to machines? What do we have to farm out to machines? How not lose human control of the process? How not become subservient to machines?
The call to action
Here are some answers, encapsulated in being more human and less of an API.
Don’t let the machines do all the thinking for you. Use your own judgment and intuition to compare and evaluate different sources and types of information. Don’t blindly accept what the machines tell you or show you. Question their assumptions, methods, and motives. Seek out alternative perspectives and opinions. Challenge yourself to find new ways of looking at old problems and new solutions to emerging challenges.
Don’t lose touch with your emotions, passions, and values. They are what make you who you are and what drive you to do what you do. They are also what connect you to other people and what make you empathetic and compassionate. Don’t let the machines numb you or distract you from what matters to you. Express yourself authentically and honestly. Share your feelings and thoughts with others. Listen to their stories and experiences. Engage in meaningful conversations and interactions.
Don’t settle for the obvious or the easy. Use your imagination and curiosity to explore new possibilities and opportunities. Don’t let the machines limit you or define you. Create your own identity and purpose. Invent your own products and services. Design your own environments and experiences. Experiment with different media and formats. Play with different ideas and concepts. Make something original and valuable.
Don’t get stuck in the past or the present. Prepare for the future and embrace change. Don’t let the machines constrain you or dictate you. Learn new skills and knowledge. Update your mental models and frameworks. Adapt to new situations and contexts. Try new things and take risks. Fail and learn from your mistakes. Grow and evolve as a person.
Don’t be passive or reactive. Take charge of your life and your future. Don’t let the machines control you or manipulate you. Make your own decisions and take your own actions. Set your own goals and pursue them. Seek out new challenges and opportunities. Initiate new projects and collaborations. Lead by example and inspire others.
These are some of the ways that you can avoid becoming an API and instead become a better human in the age of super microwaves, quantum computers and Minority Report-like decisions. These are not easy tasks, but they are essential if you want to thrive and flourish in this rapidly changing world. They are also rewarding and fulfilling, as they will help you discover and express your true potential and purpose.
This framework delineates a spectrum of human-machine interaction, from human-only tasks to hybrid models where machines augment human efforts without supplanting them. The crucial takeaway is the deliberate exclusion of scenarios where machines manage humans, emphasizing the importance of human oversight and creativity.
Develop competencies in “afternoon” subjects. For many of us, we were heavily trained in the “morning” natural sciences such as biology, chemistry, and physics while being less trained in the “afternoon” social sciences such as sociology, management, and communication sciences. More human less machine will mean competencies in the latter.
We also covered these topics at the recent 2024 Mayo Clinic Education and Technology Forum.
Questions to consider.
- How are you assessing human competencies in the clinical learning environment?
- How are you assessing machine competencies in the clinical learning environment?
- How are you assessing fusion competencies in the clinical learning environment?
- How are you developing faculty in fusion competencies?
About the authors:
DR. Daniel Cabrera, MD, is the leader of the new Mayo Clinic Advanced Digital Education Laboratory, that develops education on fusion skills for the workforce, coordinates educational initiatives, creates advanced educational tools, and innovates in the use of artificial intelligence in all its forms. He is also part of the Platform for Knowledge Solutions in Emergency Medicine at Mayo Clinic, which designs and implement innovative and effective ways to improve the creation, dissemination, and application of medical knowledge in emergency medicine.
Dr. Felix Ankel is an attending physician at Regions Hospital in Saint Paul, Minnesota, and Professor of Emergency Medicine at the University of Minnesota. He is a former residency director, Accreditation Council of Graduate Medical Education (ACGME) designated institutional official (DIO), and Council of Emergency Medicine Residency Directors (CORD) board member. He currently serves as a director for the American Board of Emergency Medicine.
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