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GCRI · هوش مصنوعی و سامانه‌های خودمختار

مرور کلی حوزه

AI and autonomous سامانه‌ها as a risk field studies how learned models, software agents and robots behave in the real world, how their behaviour can be measured and how their failures propagate into the institutions, infrastructures and lives that depend on them. This page defines the field, explains why it matters for society, sets out what experts study and shows how it connects to other risks.

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01Definition

From algorithms to deployed systems.

یادگیری

Models and data

How training data, objectives and architectures shape behaviour, including failure modes.

اطمینان

Evaluation and oversight

How سامانه‌ها are tested, monitored and kept under meaningful human control.

Embodiment

Autonomy in the world

How sensing, planning and control interact in robots and vehicles.

The field combines هوش مصنوعی و یادگیری ماشین, the methods by which systems learn from data, with AI evaluation and assurance engineering, the engineering discipline of testing and assuring them. It extends to رباتیک و خودکارسازی, where AI controls physical machines, and to high-performance, cloud and edge computing, the infrastructure that trains and runs models.

As a risk field it is defined by consequences: what happens when a model generalises badly, when an agent misuses a tool, when a robot misreads its environment, or when many systems share the same flaw. علوم اجتماعی و رفتاری is part of the field because the effects of AI depend on how people use, trust and contest it.

02پایش

Field overview.

The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.

Field overview: the screen’s structure, terms and states for AI and autonomous systems.نام‌ها نمونه و مقادیر تبیینی‌اند؛ طرحی است، نه سابقه یا سامانهٔ زنده.
03Why it matters

AI is becoming infrastructure.

  • AI is moving from advisory tools to سامانه‌ها that act, through software agents and physical autonomy.
  • Public services increasingly use automated systems in decisions about people’s rights and access.
  • A small number of model providers, cloud platforms and chip supply chains underpin many applications.
  • Evaluation science lags capability, so claims about safety and performance are often hard to check.
04What experts study

The core questions.

  1. 01

    Measurement

    Do evaluations measure what they claim, and do results generalise? See ارزیابی مدل.

  2. 02

    Action

    How should authority be delegated to سامانه‌ها that act? See سامانه‌های عامل‌محور and Autonomous physical systems.

  3. 03

    Security

    How can models be attacked, and how can AI change cyber offence and defence? See AI and cyber security.

  4. 04

    کاربرد

    How does AI change science and public services? See هوش مصنوعی در علم and AI and public services.

  5. 05

    Foundations and effects

    What does AI depend on, and whom does it affect? See رایانش و انرژی and Labour and social effects.

05Connections

How AI touches other risks.

AI connects to cybersecurity, energy, labour markets, finance and public trust. وابستگی‌ها و پیامدها explains those links. Governance is convened through هوش مصنوعی و حکمرانی دیجیتال at The Global Risks Forum (GRF), and financial-sector ریسک مدل is studied through AI and Financial Model Risk at The Global Risks Alliance (GRA).

06صفحه‌ها

Pages in Field overview.

07پرسش‌ها

پرسش و پاسخ.

Is this field the same as AI ethics?
It overlaps, but its focus is measurable behaviour and failure: validity, robustness, security, reliability and effects, studied with scientific methods.
Which methods does the field rely on?
Machine learning, AI assurance engineering, computing, probability and statistics, cybersecurity, social science and robotics. Each is described on صفحهٔ بنیان STEM.
Does the field cover military AI?
The platform’s scope is civilian systems and their public effects. It does not work on weapons development.
گزارش‌هامشارکت

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گزارش‌ها is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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