The End Of Knowledge - Vault 4/2 - AI For Good - 2017

graph LR classDef foundations fill:#d3f4ff, font-weight:bold, font-size:12px classDef perspectives fill:#ffd3e0, font-weight:bold, font-size:12px classDef challenges fill:#d3ffd4, font-weight:bold, font-size:12px classDef applications fill:#fff3d3, font-weight:bold, font-size:12px classDef workforce fill:#f3d3ff, font-weight:bold, font-size:12px classDef reliability fill:#f9f9d4, font-weight:bold, font-size:12px classDef collaboration fill:#d4f9d4, font-weight:bold, font-size:12px A[State of Play] A --> B[Session establishes AI
foundations for humanity. 1] B --> C[Optimism, disquiet about
AIs job impact. 2] C --> D[Ensuring AI enhances
well-being daunting. 3] A --> E[Dr. Chan welcomes
learning from AI experts. 4] E --> F[AI to revolutionize
healthcare delivery, ethics lag. 5] A --> G[Many unanswered questions
about AI in healthcare. 6] G --> H[AI in healthcare
needs broader perspectives. 7] A --> I[Promoting AIs advantages
in resource-poor areas hard. 8] I --> J[Smartphones ubiquitous,
even in poor settings. 9] A --> K[Population aging, urbanization
shape global health. 10] K --> L[Non-communicable diseases
leading worldwide killers. 11] A --> M[Dr. Chan challenges AI
for healthy behaviors. 12] M --> N[Non-communicable diseases affect
all incomes, costly. 13] A --> O[Chronic disease management
strains health workforce. 14] O --> P[40 million new health workers
needed by 2030. 15] A --> Q[Anti-globalization driven by
technology eliminating jobs. 16] Q --> R[AI organizes messy health
data for decisions. 17] A --> S[AI applications: drug discovery,
medical analysis. 18] S --> T[Smartphone symptom checkers,
home-based sensor therapies. 19] A --> U[Medical decisions complex,
need human context. 20] U --> V[AI aids, not replaces,
doctors, nurses. 21] A --> W[Early diagnosis needs accessible,
affordable treatment. 22] W --> X[Liability issues for AI
misdiagnosis, regulation needed. 23] A --> Y[Reliability of AI questioned,
privacy issues. 24] Y --> Z[Developing countries lack
health data for AI. 25] A --> AA[AI has potential
but needs precautions. 26] AA --> AB[Consider AI beyond wealthy,
well-resourced settings. 27] A --> AC[AI potential shown by
smartphones in poor areas. 28] AC --> AD[AI could tackle chronic diseases,
access needed. 29] A --> AE[Regulation, reliability, privacy
require multisectoral collaboration. 30] class B,C,D foundations class E,F perspectives class G,H challenges class I,J challenges class K,L perspectives class M,N perspectives class O,P workforce class Q,R challenges class S,T applications class U,V challenges class W,X reliability class Y,Z reliability class AA,AB perspectives class AC,AD challenges class AE collaboration

Resume:

1.- The session aims to establish foundations to ensure AI research benefits humanity, rather than speculate about the future.

2.- There is both optimism and disquiet about AI's impact on jobs, equality, and whether it will create a less human-centric world.

3.- Ensuring AI enhances human well-being is a daunting task with no guarantees, requiring understanding of the current situation and needed initiatives.

4.- Dr. Margaret Chan, WHO Director-General, welcomes the opportunity to learn from AI experts despite admitting limited knowledge herself.

5.- Market analysts predict AI will revolutionize healthcare delivery, but ethical and policy implications have not kept pace with technological advances.

6.- Many questions remain unanswered about AI in healthcare and we may not even know all the right questions to ask yet.

7.- Enthusiasm for AI in healthcare reflects wealthy country and private company perspectives - a broader view considering resource gaps is needed.

8.- Many health facilities Dr. Chan has visited lack basics like electricity and water, so promoting AI's advantages there is hard.

9.- However, smartphones are ubiquitous even in resource-poor settings, showing the blurred line between health in rich and poor countries.

10.- Health everywhere is being shaped by population aging, rapid urbanization, and globalized marketing of unhealthy products.

11.- Non-communicable chronic diseases have overtaken infectious diseases as the leading killers worldwide, profoundly shaped by behaviors and environments.

12.- Dr. Chan wears a smartwatch herself and challenges AI experts to develop tools to empower healthy choices and behaviors.

13.- Non-communicable diseases are "democratic", affecting all incomes and places, and very costly. AI could potentially help improve lifestyle choices.

14.- Chronic disease management is putting unsustainable pressure on the already overloaded health workforce, especially as populations age.

15.- 40 million new health workers will be needed by 2030 just for chronic diseases in wealthy countries; developing countries face major shortfalls.

16.- Anti-globalization is partly driven by technology eliminating jobs. AI in healthcare could reduce overload burdens without threatening medical jobs.

17.- Health data is often messy and unstructured; AI can help organize it to guide medical decisions by detecting patterns.

18.- Potential AI applications include accelerating drug discovery, analyzing medical scans and samples, aiding diagnosis/prognosis, and enhancing patient safety.

19.- Personal smartphone symptom checkers and home-based sensor therapies are being developed to cut healthcare costs and improve access.

20.- However, Dr. Chan has reservations: Medical decisions are complex, depending on context, values, care and compassion that machines can't replicate.

21.- AI cannot replace doctors and nurses in patient interactions, only aid their work by organizing/streamlining processes.

22.- Early diagnosis enabled by AI is not helpful without accessible, affordable treatment - context and people's lives must be considered.

23.- Liability issues arise if AI misdiagnoses - can you sue a machine for malpractice? Regulation is needed before AI reaches market.

24.- Reliability of AI monitoring devices is already being questioned; history shows rejected technologies created false security. Privacy issues must be addressed.

25.- Developing countries may lack the health data for AI to mine in the first place as they still lack basic information systems.

26.- In summary, AI has huge healthcare potential but many precautions are needed. More meetings enabling exchange between sectors would help.

27.- Dr. Chan emphasizes the need to take a broader perspective beyond just wealthy, well-resourced settings when considering AI impacts.

28.- Smartphones' ubiquity even in poor areas shows potential for AI, but massive resource gaps in electricity, water, staff can't be ignored.

29.- Demographic shifts and unhealthy environments are enabling chronic diseases AI could tackle, but access and affordability must be addressed.

30.- Crucial unanswered questions remain around regulation, reliability, privacy and context that require ongoing multisectoral collaboration to address as AI advances.

Knowledge Vault built byDavid Vivancos 2024