Risques systémiques et opportunités — AGI, sécurité et compétitivité

Le paradoxe : Opportunité énorme + Risques énormes

Risque 1 : AGI (Artificial General Intelligence)

Q : Could AI eventually surpass human intelligence in all domains ?

Timeline : Experts divided

Conservative : 10-20 years (Yann LeCun)
Aggressive : 5-10 years (Eliezer Yudkowsky)
Maybe never : (some researchers skeptical)

If AGI arrives :

Changes everything (economy, society, power structures)
Control becomes critical (can we align it ?)
Arms race (countries race to build it first)

Your role : Too early to panic. But pay attention to AGI research.

Risque 2 : Concentration du pouvoir

Current state : 5 companies control the best models

Anthropic (Claude)
OpenAI (GPT)
Google (Gemini)
Meta (Llama)
Others

Risk :

Few winners control infrastructure
→ Economic power concentrates
→ Smaller companies become dependent
→ Innovation monoculture

Mitigation : Open-source movement, EU regulation push for interop.

Risque 3 : Weaponization & misuse

Current examples :

Deepfakes for misinformation
AI used for social engineering (scams)
Autonomous weapons systems

Future risks :

Mass surveillance (video analysis at scale)
Cognitive hacking (manipulate via personalization)
Biological threats (AI generates bioweapons ideas)

Mitigation : International agreements, safety research.

Risque 4 : Labor displacement (real)

2024-2026 reality :

Some jobs are getting automated (data entry, junior coding)
But net job creation from AI tools
Skill gap = displacement risk

Who's at risk :

Content creators (if AI can do it as well)
Data analysts (repetitive tasks automated)
Junior developers (less entry-level work)
Call center agents (triage automated)

Who's safe/growing :

AI specialists (demand ↑↑↑)
Strategy roles (human judgment critical)
Creative roles (AI assists, human decides)

Mitigation : Reskilling programs, safety nets, education.

Opportunity 1 : Productivity revolution

AI could increase human productivity 2-10x.

If productivity ↑ 5x :
- Same work in 1/5 the time
- OR 5x more output in same time

Macro impact :
- GDP growth
- Wealth creation
- More time for creative/family
- More resources for problems (climate, health)

Opportunity 2 : Scientific acceleration

AI already helping :

Drug discovery (AlphaFold for protein folding)
Climate models (better prediction)
Materials science (new materials)

Potential :

Cure for Alzheimer's
Fusion energy breakthrough
Carbon removal at scale

Opportunity 3 : Democratization

AI tools are getting cheaper and better.

2020 : AI = $M per model
2024 : AI = $ per API call
2027 : AI = free/cheap utility

Impact : 
- Startups can compete with big tech
- Developing countries gain access
- Individual creators can scale

Strategic question : Are you leading or following ?

Leader posture

- Invest 2-5% of revenue in AI R&D
- Build AI-native products
- Hire specialists
- Become AI-first company
- Risk : High, but first-mover advantage

Follower posture

- Wait for tools to mature
- Adopt proven solutions
- Integrate + optimize
- Stay nimble
- Risk : Lose market share if market shifts

Your choice depends on

Factor	Leader	Follower
Runway	3+ years	1+ year
Market	High risk tolerance	Stable, proven
Talent	Can attract AI talent	Standard talent
Appetite	Experimentation	Execution

Upside scenario (most likely)

2026-2027 :
- AI becomes mainstream
- Early adopters have 5-10 year head start
- Knowledge worker productivity +3x
- New jobs created (agent management, AI ops, strategy)
- Winners & losers clear in each industry

2030+ :
- AI is utility
- Competitive advantage = not using AI (if you can)
- Wealth distributed (some argue, others see concentration)

Downside scenario (less likely but possible)

- AGI breakthrough → alignment failure
- Misuse escalates (bioweapons, mass surveillance)
- Regulatory overcorrection (slows innovation)
- Economic disruption (unemployment spike)

Mitigation : Monitor research, support safety orgs, advocate for good policy