Manifesto for real AI and algorithmic transparency and openness

Transparency is regularly cited as a core principle of ethical AI, responsible AI, and trustworthy AI. 

However, rhetoric and reality are often poles apart, with transparency approached in a partial, piecemeal, and reactive manner. 

AIAAIC's manifesto sets out why real AI and algorithmic transparency and openness is needed, and what it should look like.

The realities of AI and algorithmic transparency today

The transparency and openness of artificial intelligence, algorithms, and automation, and of the organisations that design, develop and deploy them, poses significant opportunities and benefits, as well as challenges and risks. 

For better or worse, AI, algorithms and automation are here to stay

• Fundamental to many people’s daily lives, shaping their experiences, beliefs, and behaviours

• Increasingly central to the daily workings of government, companies, media, and other organisations

• Reflect the people who design, build, and manage them

The risks of AI, algorithmic and automation are increasing

• Systems are becoming larger and more complex

• Fragmented standards, little legislation

• Understanding, confidence and trust in AI, algorithms and automation are low

• Expectations of fair, transparent, and accountable systems are rising

• Scrutiny by legislators, regulators, NGOs, and the media is increasing

• Societal, environmental and reputational risks are escalating

Many AI, algorithmic and automation systems are opaque and unaccountable

• Typically, users have little or no idea how the systems they are using or are being assessed, nudged or manipulated by work 

• Equally, they may not know they are interacting with AI, algorithms and automated systems at all

• The actual or potential workings, limitations, risks and impacts of AI, algorithmic and automation systems are often concealed, disguised, or deflected

• Many AI and algorithmic systems are unavailable for meaningful external analysis or investigation

AI, algorithmic and automation transparency efforts lack substance

• User information tends to be narrow, skin-deep, and piecemeal

• Feedback, complaint and appeal systems are slow and partial

• Remain largely the preserve of technology experts

Transparency and openness are two-edged swords

• Opportunity to build confidence, esteem, and trust

• Increases visibility and expectations whilst exposing AI systems to manipulation, fraud, legal liability, and loss of IP

• Facilitates and shapes AI and algorithmic governance and ethical decision-making - for better or worse

• Requires compromise/trade-offs.

Principles of real AI and algorithmic transparency and openness

Having weighed the limitations and consequences of transparency with organisational, technical, individual, societal and other risks, every organisation designing, developing or deploying AI, algorithmic, or automation systems should adopt the following four principles: 

Meaningful

• Provide clear, concise, accurate, timely, and usable information 

• Consistent across all channels and to all audiences 

• Responsive to feedback, complaints, and appeals

• Honest, including during incidents, crises, and controversies

Verifiable 

• Provide reasonable third-party expert access to data, code, and model 

• Make third-party audit and investigatory reports public

Inclusive

• Involve users and other relevant stakeholders in system design, development, and deployment

• Provide formal feedback loops to relevant audiences, and share feedback as widely as possible

Accessible

• To all relevant users, including the disabled, the elderly, non-internet users, and other disadvantaged people 

• Visible at the first point of contact with the system, and across all relevant touchpoints.

October 4, 2021