GLOBAL AI REGULATION – INTERNATIONAL
News: HAP to take AI governance global
What is in the news?
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Recently, the G-7
Hiroshima Leaders’ Communiqué initiated the Hiroshima AI Process (HAP), an
effort by this bloc to determine a way forward to regulate Artificial
Intelligence.
What is AI?
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AI is an emerging
technology that facilitates intelligence and human capabilities of sense,
comprehend, and act with the use of machines.
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For example, Siri is a
human-like reasoning displayed by computer systems.
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Applications of AI
include natural language processing, speech recognition, machine vision and
expert systems. Examples include manufacturing robots, self-driving cars,
marketing chat bots, etc.
Why the global AI regulations necessary?
1. Bias and discrimination:
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AI systems can inherit
biases from the data they are trained on, leading to discriminatory outcomes.
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For example, facial recognition algorithms have been
shown to have higher error rates for women and people with darker skin tones.
2. Accountability issues:
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The responsibility and
accountability for AI decisions can be unclear, especially when complex systems
are involved. This poses challenges in determining
liability in case of AI-related accidents or harm caused by AI systems.
3. Black box process:
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Some AI tools are so
complicated that they are like a "black box." This means that even
the people who create them can't fully understand how they work and how they
come up with certain answers or decisions.
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It's like a secret box
that generates an output, but nobody knows exactly how it does it.
4. Security risks:
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AI systems can be
vulnerable to cybersecurity threats and attacks. Adversarial attacks can
manipulate AI models to produce incorrect or malicious results, posing risks in
critical domains such as autonomous vehicles or healthcare.
5. Ethical considerations:
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AI raises ethical
questions related to the impact on jobs, social inequality, and the
concentration of power. For example, automated
decision-making in hiring processes may perpetuate existing biases and
result in unfair outcomes.
Concerns:
1. International cooperation:
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Developing consensus
among the countries with varying priorities and issues can be a complex task.
2. Speed of development:
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Often the countries’
regulations cannot compete with the speed of the development of new
technologies and their evolution.
3. One size fits all approach:
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Because AI is a
multi-faceted capability, “one-size-fits all” regulation will over-regulate in
some instances and under-regulate in others.
4. Accountability and liability:
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Determining
responsibility and liability when AI systems cause harm or make erroneous
decisions can be challenging. Clarifying the legal frameworks and
accountability structures surrounding AI is crucial for effective regulation.
WAY FORWARD:
1. International Cooperation:
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Given that various
governments have only recently established AI policies, and in some cases are
still formulating them, international cooperation is still very much a work in
progress. in the setting of standards at the multilateral level. Example -
Globally, consensus agreements like the Paris climate agreement can be enacted
to regulate AI.
2. Common Rule Book:
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It is a recognition that
AI related technologies cannot continue to operate without a common rulebook.
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Over the coming months
and years, the UNESCO Agreement’s recommendation will serve as a compass to
guide governments and companies, to voluntarily develop and deploy AI
technologies that conform with the commonly agreed principles.
3. Industries self-regulation:
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Companies involved in AI
development should take responsibility for ensuring the ethical and responsible
use of their technologies.
4. Promotion of transparency:
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The AI system process
should be more transparent as it should provide the details of the decision
making and process mechanism.
5. Inclusive approach:
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The global AI regulation
should cover all the people and all the countries. The regulations should also
resolve problems like data privacy, accountability issues and black box process
methic.