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1、1 Interim Report:Governing AI for Humanity December 2023 www.un.org/en/ai-advisory-body Introduction 2 The Global Governance Deficit 6 Opportunities and Enablers 6 Key enablers for harnessing AI for humanity 8 Governance as a key enabler 9 Risks and Challenges 10 Risks of AI 10 Challenges to be addr
2、essed 13 International Governance of AI 14 The AI governance landscape 14 Toward principles and functions of international AI governance 15 Preliminary Recommendations 16 A.Guiding Principles 16 Guiding Principle 1.AI should be governed inclusively,by and for the benefit of all 16 Guiding Principle
3、2.AI must be governed in the public interest 16 Guiding Principle 3.AI governance should be built in step with data governance and the promotion of data commons 17 Guiding Principle 4.AI must be universal,networked and rooted in adaptive multi-stakeholder collaboration 17 Guiding Principle 5.AI gove
4、rnance should be anchored in the UN Charter,International Human Rights Law,and other agreed international commitments such as the Sustainable Development Goals 17 B.Institutional Functions 18 Institutional Function 1:Assess regularly the future directions and implications of AI 20 Institutional Func
5、tion 2:Reinforce interoperability of governance efforts emerging around the world and their grounding in international norms through a Global AI Governance Framework endorsed in a universal setting(UN)20 2 Institutional Function 3:Develop and harmonize standards,safety and risk management frameworks
6、 21 Institutional Function 4:Facilitate development and use of AI for economic and societal benefit through international cooperation 21 Institutional Function 5:Promote international collaboration on talent development,access to compute infrastructure,building of diverse high quality datasets and A
7、I-enabled public goods for the SDGs 21 Institutional Function 6:Monitor risks,report incidents,coordinate emergency response 22 Institutional Function 7:Compliance and accountability through binding norms 22 Conclusion 25 Next Steps 25 Annexes 27 About the High-Level Advisory Body 27 Members of the
8、High-Level Advisory Body on AI 28 Terms of Reference for the High-level Advisory Body on AI 29 Working Groups and Cross-Cutting Themes 30 List of Abbreviations 31 Introduction 1.Artificial intelligence1(AI)increasingly affects us all.Though AI has been around for years,capabilities once hardly imagi
9、nable have been emerging at a rapid,unprecedented pace.AI offers extraordinary potential for good from scientific discoveries that expand the bounds of human knowledge to tools that optimize finite resources and assist us in everyday tasks.It could be a game changer in the transition to a greener fu
10、ture,or help developing countries transform public health and leapfrog challenges of last mile access in education.Developed countries with ageing populations could use it to tackle labour shortages.2.Yet,there are also risks.AI can reinforce biases or expand surveillance;automated decision-making c
11、an blur accountability of public officials even as AI-enhanced disinformation threatens the process of electing them.The speed,autonomy,and opacity of AI systems challenge traditional models of regulation,even as ever more powerful systems are developed,deployed and used.3.The opportunities and the
12、risks of AI for people and society are evident and have seized public interest.They also manifest globally,with geostrategic tensions over access to the data,compute,and talent that fuel AI,with talk of a new AI arms race.Nor are the benefits and risks equitably distributed.There is a real danger,ev
13、en if humanity harnesses only the positive aspects of AI,that those will be limited to a club of the rich.1 Per OECD definition:https:/oecd.ai/en/wonk/ai-system-definition-update 3 Todays AI benefits are accruing largely to a handful of states,companies,and individuals.4.This technology cries out fo
14、r governance,not merely to address the challenges and risks but to ensure we harness its potential in ways that leave no one behind.A key measure of our success is the extent to which AI technologies help achieve the Sustainable Development Goals(SDGs).As an example,Box 1 illustrates AIs potential i
15、n tackling climate change and its impact(SDG 13).Box 1:Case study illustrating how AI can help address climate change The critical intersection of climate change and AI opportunity a case study:Climate change represents a global and universal challenge one where a collective response requires sustai
16、nable digital transformation,thoughtfully designed new infrastructure,and the ability to deliver precise decision making at scale.AI-driven approaches are particularly well suited to this challenge,integrating key developments in machine learning,large language models,high quality data analysis,and
17、more,to create new capacities.Information that describes disconnected and disparate phenomena from geospatial imaging,distributed sensors,real time monitoring,and citizen-reported data on effects of hyperlocal climate change can be used to create new understanding of inputs,consequences,and the comp
18、lex systems which drive climate outcomes.Taken together with predictive systems that can transform data into insights and insights into actions,AI-enabled tools may help develop new strategies and investments to reduce emissions,influence new private sector investments in net zero,protect biodiversi
19、ty,and build broad-based social resilience.This can apply to other SDGs.The following is a non-exhaustive list of early promises of AI helping to address climate change:Assigning responsibility for climate action to national and subnational governance institutions by creating new and highly granular
20、 predictive resources for climate investment.For example,real time heatmaps of storm-related urban flooding to unlock hyperlocal infrastructure improvements in sewer and drainage systems.Building public,open-source data and AI systems to move private sector net zero reporting from a static complianc
21、e function to a public facing,real time data repository to increase trust,transparency,and accountability for public commitments.Using advanced climate modelling tied to information about urban mobility and behaviour patterns to create new early warning systems,allowing for more effective delivery o
22、f post conflict/disaster relief and recovery.Developing evidence-based AI interventions in open system and other carbon removal technologies where high uncertainty intervals can limit crucial early-stage investment.Advanced modelling techniques can lower the cost of scientific inquiry and allow for
23、rapid prototyping of novel solutions.But structural barriers remain to help these technologies reach the scale required to match the scope of the climate crisis and meet the diverse needs of the many critical stakeholders in the climate fight including corporations,governments,activists,civil societ
24、y,and others.Systemic 4 risks such as algorithmic bias,transfer context bias,interpretation bias,representation and allocation harms would have to be considered.Some actions to overcome barriers include:Improving model explainability and trust in order to increase adoption of AI-produced insights in
25、to critical climate decision making.Ensuring that AI models are trained on diverse,truly representative datasets,which reflect both commercially viable data collected by for-profit entities and data which“fills in the gaps”funded by nonprofit,philanthropic,and government resources and complements lo
26、cal tacit knowledge.Providing communities impacted by climate change vulnerabilities access to AI-generated predictions that would otherwise only be provided to private companies.Lowering cost of compute and machine learning expertise so that nonprofits and civil society can build and sustain free a
27、nd open AI products.Overcoming siloed action from multiple organizations building proprietary solutions/holding proprietary data to compete for private or philanthropic investment.Financing for scaling such solutions The cross-domain connection between AI and frontline experience of climate change i
28、s critical to enabling these transformative approaches.Solutions which exist in a technical silo even when enabled with compute,data,and talent face significant challenges in uptake and distribution when they do not reflect the lived experience of community members and local decision makers.For each
29、 of the opportunities described above,critical early inputs from non-technical stakeholders need to inform project conception,design,execution,and integration.Enablers therefore require a values-based approach that prioritizes community interests,a combination of technical and problem-based expertis
30、e,and a comprehensive approach to new AI development.We also need to keep an eye on the potential negative impact of AI on climate change because of the associated energy and water consumption.5.The High-level Advisory Body on AI was formed to analyse and advance recommendations for the internationa
31、l governance of AI.We interpret this mandate not merely as considering how to govern AI today,but also how to prepare our governance institutions for an environment in which the pace of change is only going to increase.AI governance must therefore reflect qualities of the technology itself and its r
32、apidly evolving uses agile,networked,flexible as well as being empowering and inclusive,for the benefit of all humanity.6.Our work does not take place in a normative or institutional vacuum.The UN is guided by rules and principles to which all of its member states commit.These shared and codified no
33、rms and values are the lodestar for all of its work,including AI governance.Norms including commitments to the UN Charter,the Universal Declaration of Human Rights,and international law including environmental law and international humanitarian law,are applicable to AI.Institutions created in suppor
34、t of multilateral objectives from peace and security to sustainable development have roles to play in cultivating the opportunities while safeguarding against risks.5 7.Nonetheless,we share the sense of urgency held by complementary governance initiatives on AI,including those by states as well as r
35、egional and intergovernmental processes such as the EU,the G7,the G20,UNESCO,and the OECD,among others.More inclusive engagement is needed,however,as many communities particularly in the Global South or Global Majority have been largely missing from these discussions,despite the potential impact on
36、their lives.A more cohesive,inclusive,participatory,and coordinated approach is needed,involving diverse communities worldwide,especially those from the Global South or Global Majority.8.The United Nations holds no panacea for the governance of AI.But its unique legitimacy as a body with universal m
37、embership founded on the UN Charter,agreed universally,as well as its commitment to embracing the diversity of all peoples of the world,offer a pivotal node for sharing knowledge,agreeing on norms and principles,and ensuring good governance and accountability.Within the UN system,plans for the Globa
38、l Digital Compact and the Summit of the Future in September 2024 offer a pathway to timely action.9.The Advisory Body comprises individuals diverse by geography and gender,discipline and age;it draws expertise from government,civil society,the private sector,and academia.Intense and wide-ranging dis
39、cussions yielded broad agreement that there is a global governance deficit in respect of AI and that the UN has a role to play.10.In this report,we first identify opportunities and enablers that can help harness the potential benefits of AI for humanity.Second,we highlight risks and challenges that
40、AI presents now and in the foreseeable future.Third,we argue that addressing the global governance deficit requires clear principles,as well as novel functions and institutional arrangements to meet the moment.The report concludes with preliminary recommendations and next steps,which will be elabora
41、ted in our final report by August 2024.11.Though we are confident of the broad direction,we know that we do not take this journey alone.We look forward to consulting widely on next steps to ensure that more voices and views are included,and that AI serves our common good.The Global Governance Defici
42、t 12.Though AI is transforming our world,its development and rewards are currently concentrated among a small number of private sector actors in an even smaller number of states.The harms are also unevenly spread.Global governance with equal participation of all member states is needed to make resou
43、rces accessible,make representation and oversight mechanisms broadly inclusive,ensure accountability for harms,and ensure that geopolitical competition does not drive irresponsible AI or inhibit responsible governance.13.The United Nations lies at the heart of the rules-based international order.Its
44、 legitimacy comes from being a truly global forum founded on international law,in the service of peace and security,human rights,and sustainable development.We believe that this 6 offers the institutional and normative foundation for collective action in global governance of AI.Apart from considerat
45、ions of equity,access,and prevention of harm,the very nature of the technology itself AI systems being transboundary in structure,function,application,and use by a wide range of actors necessitates a global approach.14.Pieces of this puzzle are being filled by self-regulatory initiatives,national an
46、d regional laws,and the work of multilateral forums.Yet,gaps remain and the challenge is clear:a global governance framework is needed for this rapidly developing suite of technologies and its use by various actors,be they the developers or users of the technology.AI presents distinctly global chall
47、enges and opportunities that the UN is uniquely positioned to address,turning a patchwork of evolving initiatives into a coherent,interoperable whole,grounded in universal values agreed by its member states,adaptable across contexts.15.The next three sections outline roles an institution or a networ
48、k of institutions anchored in the UNs universal framework could play in expanding the benefits of AI and mitigating its risks,as well as the principles and functions that will best achieve these ends.Opportunities and Enablers 16.AI has the potential to transform access to knowledge and increase eff
49、iciency around the world.A new generation of innovators is pushing the frontiers of AI science and engineering.AI is increasing productivity and innovation in sectors from healthcare to agriculture,in both advanced and developing economies.Alongside such growth are questions about which enablers are
50、 required to ensure benefits are spread equitably and safely across humanity,and that disruptive impacts,including on jobs,are addressed and managed.An important question for policy makers is how to grow successful AI ecosystems around the world while holding established and emerging players account
51、able.Box 2:Examples of AI opportunities Examples of AI opportunities People-assistive AI AI can assist people in everyday tasks as well as their most ambitious,creative and productive endeavours.People-assistive AI includes accessibility tools and improvements to education.Applications have been dev
52、eloped to serve as virtual assistants for people with limited vision or speech,supporting accessibility needs previously overlooked or neglected.AI-powered translation now covering over a hundred languages promotes access as well as intercultural understanding and communication.A new generation of t
53、utoring apps promises to expand access to quality education worldwide.Sectoral opportunities 7 AI will have a greater impact in some sectors rather than others.Among the most promising are agriculture and food security,health,education,protection of the environment,resilience to natural disasters an
54、d combating climate change.For example,AI has been used to create early-warning systems for floods,now covering over 80 countries,as well as wildfires,and food insecurity.AI is being used to monitor endangered species(e.g.,dolphins,whales)and to optimize agricultural practices.Within each field,ther
55、e are myriad possibilities.AI is broadening access to quality care,for example in the maternal health care space in Sub-Saharan Africa.Similarly,possibilities exist with respect to environmental problems,making education more accessible,helping ease poverty and hunger,and making cities safer.Scienti
56、fic opportunities AI is transforming the way in which scientific research is performed and is expanding the frontier of scientific advancement,including by accelerating molecular and genomic research.AI systems show special promise for accelerating the work of scientists across many disciplines and
57、a potential paradigm shift in the way science is practised,from helping explore new discovery spaces to automating experimentation at scale.For example,AI-powered tools that predict protein structures are being used by over a million researchers for drug discovery and to advance understanding of dis
58、eases like tuberculosis,as well as many previously neglected diseases.In the healthcare space,AI is powering diagnostic tools to help doctors with more timely detection of various types of cancers and eye-related diseases,thereby saving lives.In the energy space,AI is playing a role in optimizing en
59、ergy systems and advancing the transition to renewable energies.For example,AI has been used to boost the value of wind energy,control tokamak plasmas in nuclear fusion,and enable carbon capture.There is scope for the UN to encourage progress in AI-enabled science by focusing attention on questions
60、worth solving for the global good.Public sector opportunities Crucially,AI may drive progress in areas where market forces alone have traditionally failed.These range from extreme weather forecasting and monitoring biodiversity,to expanding educational opportunities or access to quality healthcare,a
61、nd optimizing energy systems.Governments and the public sector can improve services for citizens and strengthen delivery for vulnerable communities by leveraging AI for social good.Opportunities for the UN to harness AI Finally,the use of AI can contribute to accelerating progress towards achieving
62、the Sustainable Development Goals and enhance the role and effectiveness of the UN in promoting sustainable development,human rights and peace and security.For example,the UN can use AI to monitor the development of crisis situations in different parts of the world including human right abuses or fo
63、r measuring progress on the SDGs.While many have noted the potential of AI to contribute to many of the 17 SDGs,many have also noted significant barriers to fully leveraging the potential of AI to help make progress.The UN and other international organizations have started to build promising AI use
64、cases and demonstrations in areas such as prediction of food insecurity,managing relief operations and weather forecasting.Key enablers for harnessing AI for humanity 17.The development of AI is now driven by data,compute,and talent,sometimes supplemented by manual labelling labour.Currently,only we
65、ll-resourced member states 8 and large technology companies have access to the first three,leading to a concentration of influence.In addition to global shortages of crucial hardware such as GPUs,there is also a dearth of top technical talent in the field of AI.It has been suggested that open model
66、development may alter this dynamic,though the impact and safety of open models is still being analysed and debated.18.The AI opportunity arrives at a difficult time,especially for the Global South.An“AI divide”lurks within a larger digital and developmental divide.According to ITU estimates for 2023
67、,more than 2.6 billion people still lack access to the Internet.The basic foundations of a digital economy broadband access,affordable devices and data,digital literacy,electricity that is reliable and affordable are not there.Fiscal space is constrained and the international environment for trade a
68、nd investment flows is challenging.Critical investments will be needed in basic infrastructure such as broadband and electricity,without which the ability to participate in the development and use of AI will be severely limited.Even outside the Global South,taking advantage of AI will require effort
69、s to develop local AI ecosystems,the ability to train local models on local data,as well as fine-tuning models developed elsewhere to suit local circumstances and purposes.19.Access and benefits must go hand in hand.Entrepreneurs in regions lagging in AI capacity require and deserve the ability to c
70、reate their own AI solutions.This requires national investments in talent,data,and compute resources,as well as national regulatory and procurement capacity.Domestic efforts should be supplemented by international assistance and cooperation not only among governments but also private sector players.
71、Rallying scientists to solve societal challenges could be a key enabler for harnessing AIs potential for humanity.Open-Source and sharing of data and models could play an important role in spreading the benefits of AI and developing beneficial data and AI value chains across borders.20.Enablers(comm
72、on rails)for AI development,deployment and use would need to be balanced with guard rails to manage impact on societies and communities.A litmus test will be the extent to which AI governance efforts yield human augmentation rather than human replacement or alienation as the outcome.Some AI developm
73、ent relies on cheap and exploitable labour in the Global South.Even in the Global North,there are questions related to valuing artistic expression,intellectual property,and the dignity of human labour.Equitable access to these technologies and relevant skills to make full use of them are needed if w
74、e are to avoid“AI divides”within and across nations.Governance as a key enabler 21.AI can and should be deployed in support of the Sustainable Development Goals.But doing so cannot rely on current market practices alone,nor should it rely on the benevolence of a handful of technology companies.Any g
75、overnance framework should shape incentives globally to promote these larger and more inclusive objectives and help identify and address trade-offs.9 22.Comparisons with other sectors offer potential lessons.Mechanisms such as Gavi,the Vaccine Alliance,may suggest short-term examples for ensuring th
76、at the benefits are shared.Repositories of AI models that can be adapted to different contexts could be the equivalent of generic medicines to expand access,in ways that do not promote AI concentration or consolidation.23.Some of these societally beneficial aspirations may be realized by advances in
77、 AI research itself;others may be addressed by leveraging novel market mechanisms to level the playing field,or by incentivizing actors to reach all communities and enable benefits to be accessible to all.But many will not.Ensuring that AI is deployed for the common good,and that its benefits are di
78、stributed equitably,will require governmental and intergovernmental action with innovative ways to incentivize participation from private sector,academia and civil society.A more lasting solution is to enable federated access to the fundamentals of data,compute,and talent that power AI as well as IC
79、T infrastructure and electricity,where needed.Here,the European Organization for Nuclear Research(CERN),which operates the largest particle physics laboratory in the world,and similar international scientific collaborations may offer useful lessons.A distributed-CERN reimagined for AI,networked acro
80、ss diverse states and regions,could expand opportunities for greater involvement.Other examples of open science relevant to AI include the European Molecular Biology Laboratory(EMBL)in biology or ITER,the International Thermonuclear Experimental Reactor.Risks and Challenges 24.Along with ensuring eq
81、uitable access to the opportunities created by AI,greater efforts must be made to confront known,unknown,and as yet unknowable harms.Today,increasingly powerful systems are being deployed and used in the absence of new regulation,driven by the desire to deliver benefits as well as to make money.AI s
82、ystems can discriminate by race or sex.Widespread use of current systems can threaten language diversity.New methods of disinformation and manipulation threaten political processes,including democratic ones.And a cat and mouse game is underway between malign and benign users of AI in the context of
83、cybersecurity and cyber defence.Risks of AI 25.We examined AI risks firstly from the perspective of technical characteristics of AI.Then we looked at risks through the lens of inappropriate use,including dual-use,and broader considerations of human-machine interaction.Finally,we looked at risks from
84、 the perspective of vulnerability.26.Some AI risks originate from the technical limitations of these systems.These range from harmful bias to various information hazards such as lack of accuracy and“hallucinations or confabulations,which are known issues in generative AI.10 27.Other risks are more a
85、 product of humans than AI.Deep fakes and hostile information campaigns are merely the latest example of technologies being deployed for malevolent ends.They can pose serious risks to societal trust and democratic debate.28.Still others relate to human-machine interaction.At the individual level,thi
86、s includes excessive trust in AI systems(automation bias)and potential de-skilling over time.At the societal level,it encompasses the impact on labour markets if large sections of the workforce are displaced,or on creativity if intellectual property rights are not protected.Societal shifts in the wa
87、y we relate to each other as humans as more interactions are mediated by AI cannot also be ruled out.These may have unpredictable consequences for family life and for physical and emotional well-being.29.Another category of risk concerns larger safety issues,with ongoing debate over potential“red li
88、nes”for AI whether in the context of autonomous weapon systems or the broader weaponization of AI.There is credible evidence about the increasing use of AI-enabled systems with autonomous functions on the battlefield.A new arms race might well be underway with consequences for global stability and t
89、he threshold of armed conflict.Autonomous targeting and harming of human beings by machines is one of those“red lines”that should not be crossed.In many jurisdictions,law-enforcement use of AI,in particular real-time biometric surveillance,has been identified as an unacceptable risk,violating the ri
90、ght to privacy.There is also concern about uncontrollable or uncontainable AI,including the possibility that it could pose an existential threat to humanity(even if there are debates over whether and how to assess such threats).30.Putting together a comprehensive list of AI risks for all time is a f
91、ools errand.Given the ubiquitous and rapidly evolving nature of AI and its use,we believe that it is more useful to look at risks from the perspective of vulnerable communities and the commons.We have attempted an initial categorization as per this approach(Box 3),which will be developed further int
92、o a risk assessment framework,building on existing efforts.There will be dynamicity about risks as technology,its adoption,and use evolve.This speaks to the need to keep risks under review through interdisciplinary science and evidence-based approaches.Adaptable risk management frameworks that can b
93、e tuned as per the experience of different regions at different times would also be needed.The UN can provide a valuable space for such mutual learning and agile adaptation.Box 3:Categorizing risks from the perspective of existing or potential vulnerability AI risks from the perspective of existing
94、or potential vulnerability Individuals o Human dignity/value/agency(manipulation,deception,nudging,sentencing)o Life,safety,security(autonomous weapons,autonomous cars,interaction with chemical,biological,radiological and nuclear defence)o Physical and mental integrity,health and safety(diagnostics,
95、nudging,neurotechnology)11 o(other)human rights/civil liberties,e.g.fair trial(recidivism prediction),presumption of innocence(predictive policing),freedom of expression(nudging),privacy(biometric recognition)o Life opportunities(education,jobs,financial stability)Groups o Discrimination/unfair trea
96、tment of sub-groups,including on basis of gender o Group isolation/marginalization o Functioning of a community o Social equality/equity(unfair treatment of groups,including on basis of gender)o Children,elderly,people with disabilities Society o International and national security(autonomous weapon
97、s/disinformation)o Democracy(elections,trust)o Information Integrity(mis-or disinformation,deep fakes,personalized news)o Rule of Law(functioning of and trust in institutions,judiciary)o Security(military and policing uses)o Cultural diversity and shifts in human relationships(homogeneity,fake frien
98、ds)o Social cohesion(filter bubbles,declining trust in news,information)Economy o Power concentration o Technological dependency o Unequal economic opportunity o Resource distribution/allocation o Under-/overuse of AI,techno-solutionism (Eco)systems o Stability of financial systems o Risk to critica
99、l infrastructure o Strain on environment/climate/natural resources Values and Norms o Ethical values o Moral values o Social values o Cultural values o Legal norms 31.There is not yet a consensus on how to assess or address these risks.Nevertheless,as the precautionary principle provides on environm
100、ental dilemmas,scientific uncertainty about risks should not lead to governance paralysis.Achieving consensus and acting on it requires global cooperation and coordination,including through shared risk monitoring mechanisms.International organizations have decades of relevant experience with dual us
101、e technologies,from chemical and biological weapons to nuclear energy,based in treaty law and other normative frameworks,that could be applied in addressing risks of AI.12 32.We also recognize the need to be proactive.There are important lessons in recent experiences with other globally scalable,hig
102、h-impact technologies,such as social media.Even as diverse societies process the impact and implications of AI,the need for effective global governance to share concerns and coordinate responses is clear.33.We must identify,classify,and address AI risks,including building consensus on which risks ar
103、e unacceptable and how they can be prevented or pre-empted.Alertness and horizon-scanning for unanticipated consequences from AI is also needed,as such systems are introduced in increasingly diverse and untested contexts.To achieve this,we must overcome technical,political,and social challenges.Chal
104、lenges to be addressed 34.Many AI systems are opaque,either because of their inherent complexity or commercial secrecy as to their inner workings.Researchers and governance bodies have difficulty in accessing information or fully interrogating proprietary datasets,models,and systems.Further,the scie
105、nce of AI is at an early stage,and we still do not fully understand how advanced AI systems behave.This lack of transparency,access,compute and other resources,and understanding hinders the identification of where risks come from,and where responsibility for managing those risks(or compensating for
106、harm)should lie.35.Despite AIs global reach,governance remains territorial and fragmented.National approaches to regulation that typically end at physical borders may lead to tension or conflict if AI does not respect those borders.Mapping,avoiding,and mitigating risks will require self-regulation,n
107、ational regulation,as well as international governance efforts.There should be no accountability deficits.36.We also need to meet member states where they are and assist them with what they need in their own contexts given their specific constraints in terms of participation in and adherence to glob
108、al AI governance,rather than telling them where they should be and what they should do based on a context to which they cannot relate.37.In addition to technical and political hurdles,these challenges exist in a broader social context.Digital technologies are impacting the software of societies chal
109、lenging governance writ large.Moreover,there are human and environmental costs of AI hardware as well as software must be accounted for throughout its lifecycle,as human lives and our environment are at the beginning and end of all AI-integrated processes.38.Besides misuse,we also note countervailin
110、g worries about missed uses failing to take advantage of and share the benefits of AI technologies out of an excess of caution.Leveraging AI to improve access to education might raise concerns about young peoples data privacy and teacher agency.However,in a world where hundreds of millions of studen
111、ts do not have access to quality education resources,there may be downsides of not using technology to bridge the gap.Agreeing on and addressing such trade-offs will benefit from international governance mechanisms that enable us to share information,pool resources,and adopt common strategies.13 Int
112、ernational Governance of AI The AI governance landscape 39.There is,today,no shortage of guides,frameworks,and principles on AI governance.Documents have been drafted by the private sector and civil society,as well as by national,regional,and multilateral bodies,with varying degrees of impact.In tec
113、hnology terms,governance efforts have been focused on data,models,and benchmarks or evaluations.Applications have also been under focus,especially where there are existing sectoral governance arrangements,say for health or dual-use technologies.These efforts can be anchored in specific governance ar
114、rangements,such as the EU AI Act or the U.S.Executive Order and they can be associated with incentives for participation and compliance.Figure 1 presents a simplified schema for considering the emerging AI governance landscape,which the Advisory Body will develop further in the next phase of its wor
115、k.Figure 1:A three-fold simplified schema for considering interoperability across different AI governance efforts 40.Existing AI governance efforts have yielded similarities in language,such as the importance of fairness,accountability,and transparency.Yet there is no global alignment on implementat
116、ion,either in terms of interoperability between jurisdictions or 14 in terms of incentives for compliance within jurisdictions.Some favour binding rules while others prefer non-binding nudges.Trade-offs are debated,such as how to balance access and safety or whether the focus should be on present da
117、y or potential future harms.Different models may also require different emphasis in governance.A lack of common standards and benchmarks among national and multinational risk management frameworks,as well as multiple definitions of AI used in such frameworks,have complicated the governance landscape
118、 for AI,notwithstanding the need for space for different regulatory approaches to co-exist reflecting the worlds social and cultural diversity.41.Meanwhile,technical advances in AI and its use continue accelerating,expanding the gap in understanding and capacity between technology companies developi
119、ng AI,companies and other organizations using AI across various sectors and societal spaces,and those who would regulate its development,deployment,and use.42.The result is that,in many jurisdictions AI governance can amount to self-policing by the developers,deployers,and users of AI systems themse
120、lves.Even assuming the good faith of these organizations and individuals,such a situation does not encourage a long-term view of risk or the inclusion of diverse stakeholders,especially those from the Global South.This must change.Toward principles and functions of international AI governance 43.The
121、 Advisory Body is tasked with presenting options on the international governance of AI.We reviewed,among others,the functions performed by existing institutions of governance with a technological dimension,including FATF,FSB,IAEA,ICANN,ICAO,ILO,IMO,IPCC,ITU,SWIFT and UNOOSA2.These organizations offe
122、r inspiration and examples of global governance and coordination.44.The range of stakeholders and potential applications presented by AI and their uses in a wide variety of contexts makes unsuitable an exact replication of any existing governance model.Nonetheless,lessons can be learned from example
123、s of entities that have sought to:(a)build scientific consensus on risks,impact,and policy(IPCC);(b)establish global standards(ICAO,ITU,IMO),iterate and adapt them;(c)provide capacity building,mutual assurance and monitoring(IAEA,ICAO);(d)network and pool research resources(CERN);(e)engage diverse s
124、takeholders(ILO,ICANN);(f)facilitate commercial flows and address systemic risks(SWIFT,FATF,FSB).45.Rather than proposing any single model for AI governance at this stage,the preliminary recommendations offered in this interim report focus on the principles that should guide the formation of new glo
125、bal governance institutions for AI and the broad functions such institutions would need to perform.The subfunctions listed in Table 1 below are informed by a survey of existing research on AI governance as well as a gap-analysis of nine current AI governance initiatives,namely,Chinas interim measure
126、s for the management of AI services,the Council of Europes draft Convention on AI,the EU AI 2 See the list of abbreviations in the annex.15 Act,the G7 Hiroshima Process,the Global Partnership on AI,the OECD AI Principles,the Partnership on AI and the Foundation Model Forum,the UK AI Safety Summit,an
127、d the U.S.Executive Order 14110.Preliminary Recommendations A.Guiding Principles Guiding Principle 1.AI should be governed inclusively,by and for the benefit of all 46.Despite its potential,many of the worlds peoples are not yet in a position to access and use AI in a manner that meaningfully improv
128、es their lives.Fully harnessing the potential of AI and enabling widespread participation in its development,deployment,and use is critical to driving sustainable solutions to global challenges.All citizens,including those in the Global South,should be able to create their own opportunities,harness
129、them,and achieve prosperity through AI.All countries,big or small,must be able to participate in AI governance.47.Affirmative and corrective steps,including access and capacity building,will be needed to address the historical and structural exclusion of certain communities,for instance women and ge
130、nder diverse actors,from the development,deployment,use,and governance of technology,and to turn digital divides into inclusive digital opportunities.Guiding Principle 2.AI must be governed in the public interest 48.The development of AI systems is largely concentrated in the hands of technology com
131、panies.The refinement,deployment and use of AI will involve other actors including but not limited to the original developers(be they companies,small AI labs,other organizations as well as countries)but include deployers and users who will range from individuals,to companies,organizations,and govern
132、ments and who will bring a wide variety of incentives to their approaches.49.As shown by the experience with social media,AI products and services can scale rapidly across borders and categories of users.For this reason,as well as wider considerations of opportunities and risks,AI must be governed i
133、n the broader public interest.“Do no harm”is necessary,but not sufficient.A broader framing is needed for accountability of companies and other organisations that build,deploy and control AI as well as those that use AI across multiple sectors of the economy and society across the lifecycle of AI.Th
134、is cannot rely on self-regulation alone:binding norms enforced by member states consistently are needed to ensure that public interests,rather than private interests,prevail.50.AI will be used by people and organizations,across multiple sectors,each with different use-cases and complexities and risk
135、s.Governance efforts must bear in mind public policy goals related to diversity,equity,inclusion,sustainability,societal and individual well-being,competitive markets,and healthy innovation ecosystems.They must also integrate implications of missed uses for economic and social development.16 Governa
136、nce in this context should expand representation of diverse stakeholders,as well as offer greater clarity in delineating responsibilities between public and private sector actors.Governing in the public interest also implies investments in public technology,infrastructure,and the capacity of public
137、officials.Guiding Principle 3.AI governance should be built in step with data governance and the promotion of data commons 51.Data is critical for many major AI systems.Its governance and management in the public interest cannot be divorced from other components of AI governance(Figure 1).Regulatory
138、 frameworks and techno-legal arrangements that protect privacy and security of personal data,consistent with applicable laws,while actively facilitating the use of such data will be a critical complement to AI governance arrangements,consistent with local or regional law.The development of public da
139、ta commons should also be encouraged with particular attention to public data that is critical for helping solve societal challenges including climate change,public health,economic development,capacity building and crisis response,for use by multiple stakeholders.Guiding Principle 4.AI governance mu
140、st be universal,networked and rooted in adaptive multi-stakeholder collaboration 52.Any AI governance effort should prioritize universal buy-in by different member states and stakeholders.This is in addition to inclusive participation,in particular lowering entry barriers for previously excluded com
141、munities in the Global South(Guiding Principle 1).This is key for emerging AI regulations to be harmonized in ways that avoid accountability gaps.53.Effective governance should leverage existing institutions that will have to review their current functions in light of the impact of AI.But this is no
142、t enough.New horizontal coordination and supervisory functions are required and they should be entrusted to a new organizational structure.New and existing institutions could form nodes in a network of governance structures.There is a clear momentum across diverse states for this to happen as well a
143、s growing awareness in the private sector for a well-coordinated and interoperable governance framework.Civil society concerns regarding the impact of AI on human rights point in a similar direction.54.Such an AI governance framework can draw on best practices and expertise from around the world.It
144、must also be informed by understanding of different cultural ideologies driving AI development,deployment,and use.Innovative structures within this governance framework would be needed to engage the private sector,academia,and civil society alongside governments.Inspiration may be drawn from past ef
145、forts to engage the private sector in pursuit of public goods,including the ILOs tripartite structure and the UN Global Compact.17 Guiding Principle 5.AI governance should be anchored in the UN Charter,International Human Rights Law,and other agreed international commitments such as the Sustainable
146、Development Goals 55.The UN has a unique normative and institutional role to play;aligning AI governance with foundational UN values notably the UN Charter and its commitment to peace and security,human rights,and sustainable development offers a robust foundation and compass.The UN is positioned to
147、 consider AIs impact on a variety of global economic,social,health,security,and cultural conditions,all grounded in the need to maintain universal respect for,and enforcement of,human rights and the rule of law.Several UN agencies have already done important work on the impact of AI on fields from e
148、ducation to arms control.56.The Global Digital Compact and the Roadmap for Digital Cooperation are examples of multi-stakeholder deliberations towards a global governance framework of technologies including AI.Strong involvement of UN member states,empowering UN agencies and involving diverse stakeh
149、olders,will be vital to empowering and resourcing a global AI governance response.B.Institutional Functions 57.We consider that to properly govern AI for humanity,an international governance regime for AI should carry out at least the following functions.These could be carried out by individual inst
150、itutions or a network of institutions.Figure 2:AI governance functions distributed by institutional hardness 18 58.Figure 2 summarizes our recommended institutional functions for international AI governance.At the global level,international organizations,governments,and private sector would bear pri
151、mary responsibility for these functions.Civil society,including academia and independent scientists,would play key roles in building evidence for policy,assessing impact,and holding key actors to account during implementation.Each set of functions would have different loci of responsibility at diffe
152、rent layers of governance private sector,government,and international organizations.We will further develop the concept of shared and differentiated responsibilities for multiple stakeholders at different layers of the governance stack in the next phase of our work.Institutional Function 1:Assess re
153、gularly the future directions and implications of AI 59.There is,presently,no authoritative institutionalized function for independent,inclusive,multidisciplinary assessments on the future trajectory and implications of AI.A consensus on the direction and pace of AI technologies and associated risks
154、 and opportunities could be a resource for policymakers to draw on when developing domestic AI programmes to encourage innovation and manage risks.60.In a manner similar to the IPCC,a specialized AI knowledge and research function would involve an independent,expert-led process that unlocks scientif
155、ic,evidence-based insights,say every six months,to inform policymakers about the future trajectory of AI development,deployment,and use(subfunctions 1-3 in Table 1).This should include arrangements with companies on access to information for the purposes of research and horizon-scanning.This functio
156、n would help the public better understand AI,and drive consensus in the international community about the speed and impact of AIs evolution.It would produce regular shared risk assessments,as well as establishing standards to measure the environmental and other impacts of AI.This Advisory Body is in
157、 a way the start of such an experts-led process,which would need to be properly resourced and institutionalised.61.The extent of AIs negative externalities is not yet fully clear.The role of AI in disintermediating aspects of life that are core to human development could fundamentally change how ind
158、ividuals and communities function.As AI capabilities further advance,there is the potential for profound,structural adjustments to the way we live,work,and interact.A global analytical observatory function could coordinate research efforts on critical social impacts of AI,including its effects on la
159、bour,education,public health,peace and security,and geopolitical stability.Drawing on expertise and sharing knowledge from around the world,such a function could facilitate the emergence of best practices and common responses.Institutional Function 2:Reinforce interoperability of governance efforts
160、emerging around the world and their grounding in international norms through a Global AI Governance Framework endorsed in a universal setting(UN)62.AI governance arrangements should be interoperable across jurisdictions and grounded in international norms,such as the Universal Declaration of Human R
161、ights(Principle 4 19 above).They should leverage existing UN organizations and fora such as UNESCO and ITU for reinforcing interoperability of regulatory measures across jurisdictions.AI governance efforts could also be coordinated through a body that harmonises policies,builds common understandings
162、,surfaces best practices,supports implementation and promotes peer-to-peer learning(subfunctions 7-10 in Table 1).A Global AI Governance Framework could support policymaking and guide implementation to avoid AI divides and governance gaps across public and private sectors,regions,and countries as we
163、ll as clarifying the principles and norms under which various organizations should operate.As part of this framework,special attention should be paid to capacity-building both in the private and public sectors as well as dissemination of knowledge and awareness across the world.Best practices such a
164、s human rights impact assessments by private and public sector developers of AI systems could be spread through such a framework,which may a need an international agreement.Institutional Function 3:Develop and harmonize standards,safety,and risk management frameworks 63.Several important initiatives
165、 to develop technical and normative standards,safety,and risk management frameworks for AI are underway,but there is a lack of global harmonization and alignment(subfunction 11 in Table 1).Because of its global membership,the UN can play a critical role in bringing states together,developing common
166、socio-technical standards,and ensuring legal and technical interoperability.64.As an example,emerging AI safety institutes could be networked to reduce the risk of competing frameworks,fragmentation of standardization practices across jurisdictions,and a global patchwork with too many gaps.Care shou
167、ld,however,be taken not to overemphasise technical interoperability without parallel movement on other functions and norms.While there is greater awareness of socio-technical standards,more research,active involvement of civil society and transdisciplinary cooperation is needed to develop such stand
168、ards.65.Further,new global standards and indicators to measure and track the environmental impact of AI as well as its energy and natural resources consumption(i.e.electricity and water)could be defined to guide AI development and help achieve SDGs related to the protection of the environment.Instit
169、utional Function 4:Facilitate development,deployment,and use of AI for economic and societal benefit through international multi-stakeholder cooperation 66.In addition to standards for preventing harm and misuse,developers and users,especially in the Global South,need critical enablers such as stand
170、ards for data labelling and testing,data protection and exchange protocols that enable testing and deployment across borders for startups as well as legal liability,dispute resolution,business development,and other supporting mechanisms.Existing legal,financial,and technical arrangements need to evo
171、lve to anticipate complex adaptive AI systems of the future,and this will require taking into account lessons learnt from forums such as FATF,20 SWIFT and equivalent mechanisms.In addition,for most countries and regions,capacity development in the public sector is urgently required to facilitate res
172、ponsible and beneficial use of AI as well as participate in international multi-stakeholder cooperative frameworks to develop enablers for AI(subfunctions 4,5 and 11 in Table 1).Institutional Function 5:Promote international collaboration on talent development,access to compute infrastructure,buildi
173、ng of diverse high-quality datasets,responsible sharing of open-source models,and AI-enabled public goods for the SDGs 67.A new mechanism(or mechanisms)is required to facilitate access to data,compute,and talent in order to develop,deploy,and use AI systems for the SDGs through upgraded local value
174、chains,giving independent academic researchers,social entrepreneurs,and civil society access to the infrastructure and datasets needed to build their own models and to conduct research and evaluations.This may require networked resources and efforts to build common datasets and data commons for use
175、in the public interest,responsible sharing of open-source models,computational resources,and scale education and training.68.Pooling expert knowledge and resources analogous to CERN,EMLB or ITER,as well as the technology diffusion functions of the IAEA,could provide a much-needed boost to the SDGs(s
176、ubfunction 6 in Table 1).Creating incentives for private sector actors to share and make available tools for research and development can also complement such functions.Experts from the Global South are often invisible at global conferences on AI.This needs to change.69.Opening access to data and co
177、mpute should also be accompanied by capacity-building,in particular in the Global South.To facilitate local creation,adoption,and context-specific tuning of models,it would be important to track positive uses of AI,incentivize and assess AI-enabled public goods.Private sector engagement would be cru
178、cial in leveraging AI for the SDGs.Analogous to commitments made by businesses under the Global Compact,this could include public promises by technology and other companies to develop,deploy,and use AI for the greater good.In the larger context of the Global Digital Compact,it could also include rep
179、orting on the ways in which AI is supporting the Sustainable Development Goals.Institutional Function 6:Monitor risks,report incidents,coordinate emergency response 70.The borderless nature of AI tools,which can proliferate across the globe at the stroke of a key,pose new challenges to international
180、 security and global stability.AI models could lower the barriers for access to weapons of mass destruction.AI-enabled cyber tools increase the risk of attacks on critical infrastructure and dual-use AI can be used to power lethal autonomous weapons which could pose a risk to international humanitar
181、ian law and other norms.Bots can rapidly disseminate harmful information,with increasingly human characteristics,in a manner that can cause significant damage to markets and public institutions.The possibility of rogue AI escaping control and posing still larger risks cannot be ruled out.Given these
182、 challenges,capabilities must be 21 created at a global level to monitor,report,and rapidly respond to systemic vulnerabilities and disruptions to international stability(subfunctions 13,14 in Table 1).71.For example,a techno-prudential model,akin to the macro-prudential framework used to increase r
183、esilience in central banking and bringing together those developed at the national level,may help to similarly insulate against AI risks to global stability.Such a model must be grounded in human rights principles.72.Reporting frameworks can be inspired by existing practices of the IAEA for mutual r
184、eassurance on nuclear safety and nuclear security,as well as the WHO on disease surveillance.Institutional Function 7:Compliance and accountability based on norms 73.We cannot rule out that legally binding norms and enforcement would be required at the global level.A regional effort for an AI treaty
185、 is already underway and the issue of lethal autonomous weapons is under consideration in the framework of a treaty on conventional weapons.Non-binding norms could also play an important role,alone or in combination with binding norms.The UN cannot and should not seek to be the sole arbiter of AI go
186、vernance.However,in certain fields,such as challenges to international security,it has unique legitimacy to elaborate norms(subfunction 12 in Table 1).It can also help ensure that there are no accountability gaps,for example by encouraging states to report analogous to reporting on the SDGs targets
187、and the Universal Periodic Review that facilitates monitoring,assessing,and reporting on human rights practices(subfunctions 15 in Table 1).This would need to be done in a timely and accurate way.Inspired by existing institutions such as the WTO,dispute resolution can also be facilitated through glo
188、bal forums.74.At the same time,the legitimacy of any global governance institution depends on accountability of that institution itself.International governance efforts must demonstrate resolute transparency in objectives and processes and make all efforts to gain the trust of citizen stakeholders,i
189、ncluding by preventing conflicts of interest.22 Table 1:Subfunctions for international governance of AI Summary table of subfunctions for international governance of artificial intelligence,and possible timeframes for realization Subfunction Description Category Possible timeframe required to instit
190、utionalise proposed subfunction 1.Scientific assessment Prepare a public review of international,regional,and national AI policies at least every 6 months.Research&Analysis 6-12 months 2.Horizon scanning Prepare a horizon-scanning report that identifies risks that transcend borders and can potential
191、ly affect all jurisdictions.Research&Analysis 6-12 months 3.Risk classification Assess existing and upcoming AI models on a risk scale of untenable,high-level,mid-level,and low to no risks.Research&Analysis 6-12 months 4.Access to benefits Equitable access to technology and benefits of AI,accelerati
192、ng achievement of the Sustainable Development Goals.Enabling 12-24 months 5.Capacity building Programs and resources to build AI technology and businesses as well as governance and promotional capacity among states.Enabling 12-24 months 6.Joint R&D Establish the capacity to undertake collaborative r
193、esearch and development of AI to benefit those who dont have access to AI tools or expertise.Enabling 12-24 months 7.Inclusive participation Ensure participation of all stakeholder groups and all countries and regions in collective governance,risk management and realization of opportunities;strive f
194、or innovative governance.Governing 6-12 months 8.Convening,international learning Convene stakeholders regularly to consider AI policies across jurisdictions;building consensus on shared vocabulary and definitions;peer to peer learning.Governing 6-12 months 23 9.International coordination Deconflict
195、ing work and building synergy across existing international bodies that continue to address AI.Governing 6-12 months 10.Policy harmonization;norm alignment Surfacing best practices for norms and rules,including for risk mitigation and economic growth.Align,leverage,and include,soft and hard law,stan
196、dards,methods,and frameworks developed at the regional,national,and industry level to support interoperability.Governing 12-24 months 11.Standard setting Develop global consensus on standards for AI use across stakeholder groups by working with national standards development organizations(SDOs)-upda
197、ted regularly.Governing 12-24 months 12.Norm elaboration Convene stakeholders to assess the necessity of and negotiate non-binding and binding frameworks,treaties,or other regimes for AI.Governing 24-36 months 13.Enforcement Develop mutual reassurance schemes,information sharing mechanisms that resp
198、ect commercial and national security information,dispute resolution mechanisms,and liability schemes/regimes.Governing 36 months 14.Stabilization and response Develop and collectively maintain an emergency response capacity,off-switches and other stabilization measures.Governing 36 months 15.Monitor
199、ing and verification Elaborate oversight and verification schemes where appropriate to ensure that the design,deployment and use of AI systems is in compliance with applicable international law.Governing 36 months Conclusion 75.To the extent that AI impacts our lives how we work and socialize,how we
200、 are educated and governed,how we interact with one another daily it raises questions more fundamental than how to govern it.Such questions of what it means to be human in a fully digital and networked world go well beyond the scope of this Advisory Body.Yet they are implicated in the decisions we m
201、ake today.For governance is not an end but a means,a set of mechanisms intended to exercise control or direction of something that has the potential for good or ill.76.We aspire to be both comprehensive in our assessment of the impact of AI on peoples lives and targeted in identifying the unique dif
202、ference the UN can make.We hope it is apparent that we see real benefits of AI;equally,we are clear-eyed about its risks.24 77.The risks of inaction are also clear.We believe that global AI global governance is essential to reap the significant opportunities and navigate the risks that this technolo
203、gy presents for every state,community,and individual today.And for the generations to come.78.To be effective,the international governance of AI must be guided by principles and implemented through clear functions.These global functions must add value,fill identified gaps,and enable interoperable ac
204、tion at regional,national,industry,and community levels.They must be performed in concert across international institutions,national and regional frameworks as well as the private sector.Our preliminary recommendations set out what we consider to be core principles and functions for any global AI go
205、vernance framework.79.We have taken a form follows function approach and do not,at this stage,propose any single model for AI governance.Ultimately,however,AI governance must deliver tangible benefits and safeguards to people and societies.An effective global governance framework must bridge the gap
206、 between principles and practical impact.In the next phase of our work,we will explore options for institutional forms for global AI governance,building on the perspectives of diverse stakeholders worldwide.Next Steps 80.Rather than proposing any single model for AI governance at this stage,the fore
207、going preliminary recommendations focus on the principles and functions to which any such regime must aspire.81.Over the coming months we will consult individually and in groups with diverse stakeholders around the world.This includes participation at events tasked with discussing the issues in this
208、 report as well as engagement with governments,the private sector,civil society,and research and technical communities.We will also pursue our research,including on risk assessment methodologies and governance interoperability.Case studies will be developed to help think about landing issues identif
209、ied in the report in specific contexts.We also intend to dive deep into a few areas,including Open-Source,AI and the financial sector,standard setting,intellectual property,human rights,and the future of work by leveraging existing efforts and institutions.82.We encourage constructive engagement fro
210、m anyone with an interest in AI.More information about how to engage with our ongoing work can be found online at https:/www.un.org/en/ai-advisory-body.83.We look forward to engaging with diverse stakeholders as we answer more fully the questions identified in this interim report,in support of the o
211、ngoing efforts of the United Nations on digital cooperation and on social progress and better standards of life in larger freedom.25 Box 4:Example of questions to be addressed during consultations on this interim report Key questions for further discussion in the next phase of work Opportunities and
212、 enablers of AI Can we make AI development more inclusive by facilitating model-building ecosystems,for example through data protection and exchange frameworks,with shared access to compute?Would common standards for data labelling and testing encourage AI startups to test and deploy across more cou
213、ntries and regions?What mechanisms would promote equitable access to compute and privacy-preserving sharing of datasets across stakeholders and member states?How can we grow and spread AI talent?Can UN entities or other institutions facilitate exchange of students,joint PhD programmes,and cross-doma
214、in(health and AI,agriculture and AI)talent development?How can international collaboration harness AI talent,data and compute for scientific research and for the SDGs?How can we incentivize governments and the private sector to invest in other core infrastructures that drive AI development around th
215、e world?Risks and challenges of AI What is the best path to reaching consensus on identifying,classifying,and addressing AI risks?How should assessments of risks and challenges relate to more specific use cases of AI,notably autonomous weapons systems?What should be the threshold or the trigger for
216、identifying red lines(analogous,perhaps,to the ban on human cloning in biomedical research)?How would any such red line be policed and enforced?International governance of AI Do the principles listed above properly reflect the aspirations that a global governance regime for AI should have?Do the fun
217、ctions outlined above properly reflect what global AI governance can and should do?26 What structural arrangement(s)would best empower a new institution or set of institutions to uphold these principles and carry out these functions?A range of models exist within the UN system for engaging industry
218、in sectoral work(WHO,ITU,ICAO etc).What kind of mechanism could best support industry participation in international governance of AI?Which of the normative,policy and information instruments that exist today could support coherence in technology governance across governments,private sector and civi
219、l society?What kind of financing and capacity building mechanisms would be needed for effective international arrangements to address the functions outlined above?27 Annexes About the High-Level Advisory Body on AI Initially proposed in 2020 as part of the Secretary-Generals Roadmap for Digital Coop
220、eration(A/74/821),The multi-stakeholder High-level Advisory Body on Artificial Intelligence was formed in October 2023 to undertake analysis and advance recommendations for the international governance of AI.Advisory Body members participated in their personal capacity,not as representatives of thei
221、r respective organizations.This proposal represents a majority consensus;no member is expected to endorse every single point contained in the document.In publishing this report,the UN AI Advisory Group members affirm their broad,but not unilateral,agreement with its findings and recommendations.Lang
222、uage included in this report does not imply institutional endorsement by the UN AI Advisory Group members respective organizations.Members of the High-Level Advisory Body on AI Carme Artigas(Co-Chair)James Manyika(Co-Chair)Anna Abramova Omar Sultan Al Olama Latifa Al-Abdulkarim Estela Aranha Ran Bal
223、icer Paolo Benanti Abeba Birhane Ian Bremmer Anna Christmann Natasha Crampton Nighat Dad Vilas Dhar Virginia Dignum Arisa Ema Mohamed Farahat Amandeep Singh Gill Wendy Hall Rahaf Harfoush Hiroaki Kitano Haksoo Ko Andreas Krause Maria Vanina Martinez Posse Seydina Moussa Ndiaye Mira Murati Petri Myll
224、ymaki Alondra Nelson Nazneen Rajani Craig Ramlal He Ruimin Emma Ruttkamp-Bloem Marietje Schaake Sharad Sharma Jaan Tallinn Philip Thigo Jimena Sofia Viveros Alvarez Yi Zeng Zhang Linghan 28 Terms of Reference for the High-level Advisory Body on AI The High-level Advisory Body on Artificial Intellige
225、nce,convened by the United Nations Secretary-General,will undertake analysis and advance recommendations for the international governance of artificial intelligence.The Bodys initial reports will provide high-level expert and independent contributions to ongoing national,regional,and multilateral de
226、bates.The Body will consist of 38 members from governments,private sector,civil society,and academia,as well as a member Secretary.Its composition will be balanced by gender,age,geographic representation,and area of expertise related to the risks and applications of artificial intelligence.The membe
227、rs of the Body will serve in their personal capacity.The Body will engage and consult widely with governments,private sector,academia,civil society,and international organizations.It will be agile and innovative in interacting with existing processes and platforms as well as in harnessing inputs fro
228、m diverse stakeholders.It could set up working parties or groups on specific topics.The members of the Body will be selected by the Secretary-General based on nominations from Member States and a public call for candidates.It will have two Co-Chairs and an Executive Committee.All stakeholder groups
229、will be represented in the Executive Committee.The Body shall be convened for an initial period of one year,with the possibility of extension by the Secretary-General.It will have both in-person and online meetings.The Body will prepare a first report by 31 December 2023 for the consideration of the
230、 Secretary-General and the Member States of the United Nations.This first report will present a high-level analysis of options for the international governance of artificial intelligence.Based on feedback to the first report,the Body will submit a second report by 31 August 2024 which may provide de
231、tailed recommendations on the functions,form,and timelines for a new international agency for the governance of artificial intelligence.The Body shall avoid duplication with existing forums and processes where issues of artificial intelligence are considered.Instead,it shall seek to leverage existin
232、g platforms and partners,including UN entities,working in related domains.It shall fully respect current UN structures as well as national,regional,and industry prerogatives in the governance of artificial intelligence.The deliberations of the Body will be supported by a small secretariat based in t
233、he Office of the Secretary-Generals Envoy on Technology and be funded by extrabudgetary donor resources.29 Working Groups and Cross-Cutting Themes The ongoing work of the Advisory Body is organized around five working groups and ten cross-cutting themes.Sectoral applications and additional themes wi
234、ll be considered in detail in the next phase.Working Groups Opportunities and Enablers Risks and Challenges Interoperability Alignment with Norms and Values International Institutions Cross-Cutting Issues Culture Equity Ethics Future of work Government capacity Gender Human Rights,Democracy,Rule of
235、Law Open-Source Societal impact Sustainability Sectoral applications and additional themes for deep dives Agriculture Education Environment Finance Health Intellectual property National Security Standard-setting 30 List of Abbreviations EMBL European Molecular Biology Laboratory EU European Union FA
236、TF Financial Action Task Force FSB Financial Stability Board G7 Group of Seven G20 Group of 20 GPAI Global Partnership on AI GPU Graphics Processing Unit IAEA International Atomic Energy Agency ICANN Internet Corporation for Assigned Names and Numbers ICAO International Civil Aviation Organization I
237、LO International Labour Organization IMO International Maritime Organization IPCC Intergovernmental Panel on Climate Change ITER International Thermonuclear Experimental Reactor ITU International Telecommunication Union OECD Organization for Economic Cooperation and Development SDG Sustainable Development Goals SWIFT Society for Worldwide Interbank Financial Telecommunication UNESCO United Nations Educational,Scientific and Cultural Organization UNOOSA United Nations Office for Outer Space Affairs