LONG
TERM RISKS OF AI – SCI & TECH
News: Confronting the long-term risks of
Artificial Intelligence
What's
in the news?
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Risk is a dynamic and ever-evolving
concept, susceptible to shifts in societal values, technological advancements,
and scientific discoveries.
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Countries must not fall into the trap of
loosening their regulatory frameworks to maintain competitiveness.
Key
takeaways:
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In the digital age, sharing personal
information has become riskier due to cyberattacks and data breaches.
●
Once fictional, AI now impacts various
sectors, bringing evolving risks that require global governance.
Short-term
risks associated with AI:
1.
Malfunction of AI Systems:
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Ensuring that AI systems do not
malfunction in their day-to-day tasks, especially in critical infrastructure
like water and electricity supply, to prevent disruptions and harm to society
2.
Immediate Dangers of Runaway AI:
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Although improbable, the potential for AI
systems to go rogue and manipulate crucial systems, leading to catastrophic
consequences even in the near future,
Long-term
risks associated with AI:
1.
AI and Biotechnology:
●
The combination of AI and biotechnology
could alter human emotions, thoughts, and desires, posing profound ethical and
societal challenges.
2.
Human-Level AI:
●
Advanced AI systems capable of human-level
or superhuman performance may emerge, potentially acting on misaligned or
malicious goals.
3.
Dire Consequences:
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Superintelligent AI with harmful
intentions could have catastrophic consequences for society and human
well-being.
4.
Ethical and Safety Concerns:
●
Developing AI with such capabilities
raises significant ethical and safety concerns.
Challenges
in Aligning AI with Human Values:
1.
Transparency and Explainability:
●
Many AI systems, particularly deep
learning models, are often seen as black boxes where it’s challenging to
understand how they make decisions.
2.
Human Control:
●
Ensuring that humans maintain control over
AI systems and that AI does not act autonomously in ways that could harm
individuals or society is a key challenge.
3.
Ethical Decision-Making:
●
Developing AI that can make ethical
decisions in complex situations, such as autonomous vehicles deciding how to
respond to potential accidents, is an ongoing challenge.
4.
Cultural and Societal Values:
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Different cultures and societies have
varying values and norms.
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Aligning AI with human values involves
navigating these differences and ensuring that AI systems respect cultural
diversity.
5.
Long-Term Considerations:
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As AI evolves and becomes more powerful,
addressing long-term ethical considerations, such as the potential for
superintelligent AI, is a critical challenge.
Importance
of global cooperation in AI Regulation:
1.
Uniform Regulation:
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AI risks are not confined by borders, and
inconsistent regulations across countries can lead to confusion and
inefficiencies.
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Global cooperation allows for the
development of uniform standards and regulations.
2.
Mitigating Global Risks:
●
Many AI-related risks, especially those
with global implications such as AI’s convergence with biotechnology or the
potential for superintelligent AI, demand a collaborative approach.
3.
Ethical Frameworks:
●
Collaborative efforts can lead to the
establishment of universally accepted ethical frameworks for AI development and
deployment.
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These frameworks can guide the responsible
and ethical use of AI, regardless of where it is developed or employed.
4.
Preventing a Race to the Bottom:
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In the absence of global cooperation,
countries may prioritize rapid AI development over safety and ethics to gain a
competitive edge.
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This race to the bottom can undermine
global AI safety efforts, making coordination crucial.
5.
Technological Divides:
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Global cooperation helps prevent
technological divides where some nations advance rapidly in AI capabilities
while others lag behind.
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Such divides can exacerbate global
inequalities and have far-reaching geopolitical consequences.