Responsible AI: It is Worth it and Can it be Achieved?

Responsible AI – is it worth it and can it be achieved?

Kay Firth-Butterfield, Head of AI and Machine Learning, World Economic Forum February

Responsible AI - A History

• DeepMind • Hawking/Russell • bostrom • ME CAIEO

IEEE

Asilomar

Forum start in 2017

What is Responsible AI?

• EarthSpecies - an example of beneficial AI BUT

• The world agrees on what is responsibility but not on how we get there

• Bias,

• Fairness,

• security reliability robustness,

• privacy,

•

Explainability/transparency

• Human agency

• Accountability

• Lawful

A Human Rights Approach? – Michelle Bachelet 2021

• Civil rights and Sonderling

• US and EU see HR differently

• China…

• Where does human rights law come from – is the UN ready

UNESCO and UNICEF and OECD but no actual human rights law which is why Sonderling’s approach is important

• Ultimately a brand value issue

USA Bill of Rights

• Safe and Effective Systems: You should be protected from unsafe or ineffective systems.

• Algorithmic Discrimination Protections: You should not face discrimination by algorithms and systems should be used and designed in an equitable way.

• Data Privacy: You should be protected from abusive data practices via built-in protections, and you should have agency over how data about you is used.

• Notice and Explanation: You should know that an automated system is being used and understand how and why it contributes to outcomes that impact you.

• Alternative Options: You should be able to opt out, where appropriate, and have access to a person who can quickly consider and remedy problems you encounter.

Generative AI making Responsible AI impossible?

Yes and is that a bad thing?

Lost civilizations

Maintaining the status quo

Where is the data from Novels and human angst

Dominance of white male thought

Indigenous and AI example

Generating content from its own content – where is the human Jobs

Is it worth it?

Undoubtedly Yes – but why?

Tipping point?

Loss of Trust

Has potential to create a slowing innovation and losing the massive benefits

Also creating more regulation which can spend years in litigation before definition is achieved

At Forum we have been turning principles of Responsible AI into action for last 5 years, mainly through development of frameworks and toolkits, in the form of soft governance - WHY

BEUC, the European Consumer Organisation, representing 44 independent national consumer associations from 32 European countries 2020 survey found that:

64%

Belgium, Italy, Portugal and Spain most people agree or strongly agree that companies are using AI to manipulate consumer decisions.

52%

France, Denmark, Germany, Poland and Sweden respondents (strongly) agree.

78% of Americans and 87% of Europeans want some or together regulation 2020.

In AI We Trust?

Now

The Future

Ways to build trust

Government with citizens

Companies with citizens

And overlaps!

Can it be Achieved?

Doubts but still worth trying

Some ideas…

What is governance and why is it important for AI?

Standards

Norms

Legislation

Lethal Autonomous Weapons – a case study

• The world needs to think about AI wholistically in regulation, but it doesn’t.

• Over 192 sets of ethical principles

• OECD, UNICEF, UNESCO, GPAI

The story of the divide world

• Less trust in AI, Government and Business – north

• South less worried – new markets – but probably follow north if we don’t do this correctly

• Influence of superpowers in global south and the AI RACE

• Add on Generative AI (ChatGPT), Dall-E, new jobs and skills, Space, etc. if AI is everywhere then governance and good thinking should be too.

Regulatory systems

• Why the choice of regulator systems matters in the big picture. Choosing the world, we want…

• US – Human Rights approach

• China – old approach – get the tech or know-how in exchange for X

• Three big systems emerging:

• EU – AI Act

• US – State and NIST

• China

• What of the rest of the world?

Our Global Network

C4IR Network

•Azerbaijan

•Brazil

•Colombia

•Israel

•Kazakhstan

•Norway

•Rwanda

•Serbia

•South Africa

•Saudi Arabia

•Turkey

•UAE

Forum Offices

•United States

•Switzerland

•Japan

•India

•China

The network connects 15 advanced and emerging economies, producing 40% of global GDP and hosting 30% of the global population.

Over 200 people serve the network, including 50 Forum staff, 50 Fellows and 120 Centre staff.  The Network is rapidly expanding and projected to double its Centres by 2024.

Multistakeholder Approach

Bring together government, industry, civil society & academia to accelerate adoption of AI in the global public interest

Accelerate the social benefits of AI

Ensure everyone has access to benefits

Mitigate negative impacts & unintended consequences

Bias

• What is bias and why does it matter. Sits at the heart of a human rights approach to AI

• Hiring – NYC act

• Loans

• Criminal justice

• ALGORITHMIC JUSTICE LEAGUE

Privacy License Plates and Abortion

Accountability and Explainability

• In the US surveillance regulation is fragmented. Not so in China. Does passing a test with 95% accuracy of algorithm mean its fine to just use the algorithm or are their social imperatives

• Auditing – IP & Competition law

• Standards – IEEE and our FRT work

• Certification – IP and competition law

Special cases story – CHILDREN

• Example – children – smart toys

• Older adults

• Persons with Disabilities

Soft Regulation

Purpose

What to do – businesses

• Board

• C-suite

• Diverse teams

• Test and test again

• Education

• Reward resp AI not fast AI

• CAIEO? Or Advisory Board

• Be able to show your GC you have rules which match the seriousness e.g. FireAid v Healthcare

• Read – Resp Tech and listen – IN AI WE TRUST?

What to do government – will depend on their politics

• Procurement

• Regulation or freedom to innovate - BALANCE

• What should regulators do – sandbox, existing law, outreach

• Soft governance

• Do they need AI for “x”

• Do they need surveillance

• Create a unified regulatory system or risk not being the dominant system – EU ACT like GDPR

Buying AI

• Hold suppliers' feet to fire – its you who are on the hook legally

• Develop a suite of questions to ask of suppliers or if you are a supplier consider how to help answer questions your customer might pose. Probably in this together

• BRAND REPUTATION and ABILITY TO EXIT

Positive Futures

• STORY - Look out for the competition – film shorts

• AI and SDGs – Mustafa Sulemann – will the battle for AI global dominance be won here? Maternal health for example.

• AI and climate – fireAId – Global Coalition against Wildfires

Responsible Use of Technology

Convening a community of executives working on Responsible AI to engage in collective problem-solving and identify different models for integrating ethics into the design, deployment and use of technology

We need to apply ethics and human rights-based approaches to every phase in the lifecycle of technology –from design and development by technology companies through to the end use and application by companies across a range of industries

Purpose – to learn from each other and learn from the stories of success and failure. The case studies which we are producing, from Microsoft, IBM, Salesforce and now Google are examples from which others, perhaps more resource constraint can learn what it takes to have the design, development and use of AI created in a Responsible manner

Hannah Darnton, BSR

What’s to lose? - Credibility with the customer, brand value and possible legal action

PODCAST – In AI We Trust?

Equity & Inclusion in AI

Fostering collaborative, action-oriented exchanges that facilitate greater consistency, credibility, and success amongst ongoing efforts by its participants resulting in a Blueprint for Equity and Inclusion in AI, to ensure that AI is developed and used responsibly and that it supports widespread societal benefits.

Inclusion is too often an afterthought in how we approach the visioning, design and implementation of new digital capabilities.

Nadjia Yousif, Managing Director and Partner, Boston Consulting Group.

Inclusion is global not merely internal to a nation or organization. Global North and South divide – Dall-E Products are much better if they are made with diverse teams and members of the team represent the demographic for whom the product is intended

Responsible Limits on Facial Recognition Technology

How can we create actionable guidelines to address human rights concerns arising from the use of facial recognition technology?

Implementing actionable guidelines to address human rights concerns arising from the use of facial recognition technology in flow management and law enforcement, addressing transparency, accountability, trust and oversight; co-designing actionable risk mitigation processes with industry actors

Human-Centred AI for Human Resources

A toolkit for HR professionals to make informed and ethical decisions in adopting AI-based tools, mitigate uses that are likely to lead to biased outcomes, and promote AI-based tools appropriate for the organizational context which empower workers and respect privacy –

As large companies innovate with a growing variety of technological tools related to talent and people strategy, questions abound as to how to ensure that technology is used responsibly and effectively.

Ani Huang, Senior Vice President, HR Policy Association

Unlocking Public Sector AI

Upskilling procurement practitioners, improving government confidence in procuring AI to better interact with and serve citizens through the comprehensive

AI Procurement in a Box toolkit

AI holds the potential to vastly improve government operations and meet the needs of citizens in new ways (…). However, governments often lack experience in acquiring modern AI solutions and many public institutions are cautious about harnessing this powerful technology. Guidelines for public procurement can help in a number of ways.

AI Procurement in a Box Toolkit

Created and tested with the UK

Scaled – Brazil, Bahrain, UAE, Rwanda and more

Why SOFT GOVERNANCE is important

Empowering AI Leadership

Providing practical sets of tools to help corporate executives understand AI’s impact on their roles, ask the right questions, and make informed decisions on AI projects.

Toolkits for corporate executives to identify the benefits of AI and how to operationalize it in a responsible way

– Board Toolkit

– C-suite Toolkit

– The importance of buy-in from senior executives

Commercial Procurement of AIbased Solutions

Commercial procurement of AI solutions bridges the buy-side and the sell-side of the procurement journey and provides unique insights that help managers and firms acquire the latest AI technologies.

Developing a toolkit for commercial organizations to evaluate AI/ML technologies through a robust procurement framework and executives to make informed and agile decisions for AI procurement

Enabling Intelligent Manufacturing

Raising awareness on the value and feasibility of industrial AI, informing decision-making on responsible implementation and scaling of AI in manufacturing, and demonstrating outcomes through tangible pilots

9% of manufacturing organizations are leveraging AI today to boost efficiency, improve agility and enable self-optimizing operations

How to engage:

– Take part in an interview on high-potential applications and enabling dimensions of AI in manufacturing

– Share a use case from your organization demonstrating the impact, feasibility and scalability of AI in manufacturing

Responsible Investment in AI

Can investors and technology companies come together to identify common metrics and tools to foster the development of trusted AI systems?

Convening the investor community and technology companies to align on business practices which effectively foster the development of trusted AI system, and developing common metrics for investors and companies to shape the trajectory of responsible AI and technology development through investment

FireAId: AI to predict and fight wildfires

The challenge:

Wildfire severity, spread and frequency have all increased as a result of climate change. This poses a growing thread to forest ecosystems and high-risk rural areas. Critical services and resources such as Health and Safety, Forestry, Natural Disaster and Emergency Relief agencies, and Rural planning are overburdened and the strain on these resources is likely to grow. There is an important need for technological innovation on three fronts: prediction, emergency response and forest management, where AI can help to predict the risky locations and the best possible strategy to mitigate fire hazards.

The opportunity: to address this worldwide issue the WEF has launched a joint initiative with key partners to mitigate wildfire risks using AI Systems, which include:

A dynamic wildfire risk map that ranks the likelihood of forest fires based on seasonal variables

Resource allocation that is optimal based on many data sources and the wildfire risk map

In case of a forest fire, a first - response proposal using pre-optimized resources and maps

Why Data & AI for Climate Adaptation

–

Climate change is accelerating: in 2022 alone we had witnessed devastation of floods in Pakistan, severe drought and heatwaves in Europe, droughts in Kenya, and catastrophic impact from Hurricane Ian, causing major disruptions around the world

– Adaptation has unprecedented urgency: COP27 put climate adaptation & resilience at forefront of agenda, acknowledging mitigation alone is no longer enough. Government and business leaders are urged to step up adaptation planning and take action now

– Huge investment is needed for adaptation, esp. in Global South: adaptation & resilience financing need is expected to reach ~$140-300B p.a. by 2030 in developing countries alone

–

Data & AI is key to accelerating adaptation efforts and driving cost efficiency: Data & AI can be applied in boosting adaptation and resilience capacity and improving cost efficiency through improved hazard projections of regionalized long-term effects (e.g., sea-level rise) or extreme events (e.g., hurricanes and droughts)

Mitigations are falling short…

Well below 2C, pursuing 1.5C Paris agreement goal

+2.6-2.8 C

Current policies

+2.4 C

Full implementation of 2028 NDCs