This is part 2 in a three-part series. See here for Part 1 [The Frog]
Health care and health professions education environments are changing in three dimensions. First, the value of a clinician is moving away from being a vessel of knowledge towards being a facilitator of collective wisdom. Second, a clinician’s professional identity is evolving from binary (you are either a physician or not a physician) to quantum (you are both a physician and informaticist or even a new identity yet to be created) Third, the center of gravity for innovation in health care and health professional education is moving from the core of historical hierarchical institutions to the periphery of non-hierarchical trust, communication, and personal learning networks.
How do we navigate this environment? What language do we use? What are some of the mental models we can apply to help in sense-making? This is a three-part about the future of medical education using the frameworks of The Frog, The Fox, and The Electric Sheep. Welcome to Part 2: The Fox.
Health professions education is changing. Professional identities and structures are changing. The HPE mascot of the past was the analytic hedgehog (you take a subject matter, break it down to component parts, analyze the component parts, and become expert in the subject). The HPE mascot of the future is the fox (you take many subject matters, identify the connections between the subjective matters, synthesize mental models of the connections to create shared understanding). Current and future learners as will need to develop the set of skills necessary to be successful and relevant in a Healthcare Industry 4.0. They need to be more like a fox, less like a hedgehog.
The set of skills necessary to be successful in the 4.0 world are commonly referred as Fusion Skills. This is a relative fluid and adaptable set of traits and skills necessary to perform in an environment defined by focus on solution of problems, constant innovation, and permanent beta approach with constant interaction, augmentation and use of AI and robots.
An introductory description of Fusion Skills is key to build the foundation of the health professional 4.0 competencies:
- Technological conceptual understanding. (The understander) Not all health care professionals need to be experts on AI, machine learning or block chain, but all professionals will need to have a conceptual basic understanding of the main concepts powering the system. (Types of AI learning, classification vs. prediction, encryption, normalization, distributed systems, etc.) Like electricity, you don’t need to have a degree in electrical engineering to use a toaster but need to know enough not to be electrocuted and to make a good toast.
- Technological explanation. (The explainer) Clinicians will need to be able to understand why the appliance is making a recommendation and a decision, both in terms of the technological underpinnings and the clinical rationale. This will need to be explained to other clinicians and patients. If the technology works as a black box, the acceptance of the recommendations will not be optimal. This is like humans, if we don’t explain our recommendations, it is less likely that others will follow them.
- Technological judgement and skepticism. (The skeptic) The performance of technology will improve exponentially and likely become better than human-driven data analysis, however it will never be perfect. Humans will need to provide skeptical support. If a model of AI is input-algorithm-output, key areas of skepticism are in the quality of inputs and quality of algorithm. Input data (appropriateness of the training and validation sets) may be wrong, the algorithm not fitted appropriately, and the system may not be contextually and humanly appropriate. Health care professionals will need to acquire the competencies to catch and stop decisions that are not appropriate. This requires an understanding of the systems as well as the context and the best interest of the patient as well as an AI governance system that includes clinicians.
- Collaboration and augmentation between humans and non-humans. (The collaborator) The movement to Industry 4.0 will be fast, but not instantaneous. It will happen in phases with increasing levels of human to non-human co-location, followed by augmentation and then by collaboration. AI and robots will be required to be taught and supervised by humans for a significant amount of time. Few of us know how to feed data into an AI system, how to check on the processing and how to provide feedback to the system. A teacher (human)-student (machine) relationship will be necessary to optimize the smart systems running healthcare. As augmentation escalates, the teacher-student relation will revert, and humans will adopt a student role. Future clinicians will require the competency to perform as teacher and as student with machines. Fluidity of these roles will be key for maximizing performance of the human and AI dyad.
- Keeping context, time and flows focus on the interest of the patients. (The advocate) One of the most important aspects of the Healthcare Professionals 4.0 will be to prevent the system to move into an extreme optimization. We (humans) need to be sure that we keep the systems focused on the best interest of the patients and society. More important than what the algorithm says is what the patient feels is aligned with their wishes. These values and wishes may not align with the optimal decision, and we must be sure we can override that pathway.
Traditionally, medicine has been built into the concept of acquiring a big deep knowledge of a particular discipline of specialty through analysis (the Hedgehog of always alpha). The education institutions aim to train experts in narrow fields based on old frameworks of knowledge creation and advancement. Current industry and educational challenges call for a different approach; we should train learners on how to learn and acquire skills from multiple disciplines more than in a specific set of knowledge and abilities and a significantly different mindset where testing, failing and constant improving is consider virtuous (always beta). A fox knows many things, but a hedgehog knows one big thing. We need to educate on how to be a Fox and acquire the mental models to be a successful one.
This is Part Two of a three-part series. Don’t miss the final post [The Electric Sheep], coming Tuesday, November 30, 2021!
- How the Healthcare Industry Will Change. How The Healthcare Industry Will Change | George Washington University (gwu.edu).
- Actor-Network Theory. Actor–network theory – Wikipedia
- American Medical Education 100 Years after the Flexner Report. N Engl J Med 2006; 355:1339-1344. DOI: 10.1056/NEJMra0554.
- The Role and Importance of Knowledge Economy as a Platform for Formation of Industry 4.0. Industry 4.0: Industrial Revolution of the 21st Century | SpringerLink
- Liminality. Liminality – Wikipedia
- Human + Machine. Human + Machine | Reimagining Work in the Age of AI | Accenture
- Living in Permanent Beta. How To Overcome The Fear Of Failure: Living In Permanent Beta | by Louis Chew | Medium
- The Clinician and Dataset Shift in Artificial Intelligence. N Engl J Med 2021; 385:283-286. DOI: 10.1056/NEJMc2104626.
- Superintelligence: Paths, Dangers, Strategies. Superintelligence: Paths, Dangers, Strategies – Wikipedia
- The Ambidextrous Organization. The Ambidextrous Organization (hbr.org)
- The Blind Spot of Institutional Leadership. Otto Scharmer.
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