In these lessons, you’ll learn about the governance landscape around AI.
In these lessons, you’ll learn about the governance landscape around AI. You will learn about AI alignment with human values and external impacts that are indirectly related to the creation and deployment of any AI system, such as environmental impacts. You will also learn about AI systems that do deliberate harm and dark patterns, deceptive design patterns that are used to influence individuals to perform an action that may not be in their best interest.
Governing bodies are the ones that assign responsibility for various IT initiatives, given business pressures, regulatory obligations, stakeholder expectations, and business needs. In terms of AI ethics, this means that the governing body is ultimately responsible for the decisions, actions, and inactions. Cultural considerations, linguistic conventions, and geographic specifics intersect with ethical AI, because it’s based on how people live and work in a particular place.
Finally, these lessons will provide an overview of eight different themes among AI principles identified by the Berkman Klein Center: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and the promotion of human values.
Learning Objectives:
- Describe the governance structure of AI systems
- Recognize the responsibility of governing bodies
- Consider cultural factors in AI ethics
Skills you’ll gain
Applications Of Artificial IntelligenceArtificial Intelligence SystemsArtificial IntelligenceData IntelligenceEnvironmental IntelligenceIntelligent SystemsWhat You'll Learn
- Describe the governance, regulation, and policy structure around AI systems
- Recognize the responsibility of governing bodies for the decisions, actions, and inactions of AI
- Examine AI alignment with human values and the unintended or unethical use of AI
- Consider cultural, linguistic, and geographic factors in AI ethics
- Identify external impacts and harms, including environmental effects and dark patterns
- Review the eight ethical AI principle themes identified by the Berkman Klein Center
Key Takeaways
- The governing body assigns responsibility for IT initiatives based on business pressures, regulatory obligations, stakeholder expectations, and business needs, and is ultimately responsible for AI decisions, actions, and inactions.
- AI ethics involves alignment with human values as well as indirect external impacts such as environmental effects.
- Dark patterns are deceptive design patterns used to influence individuals to perform an action that may not be in their best interest.
- Cultural considerations, linguistic conventions, and geographic specifics intersect with ethical AI because it is based on how people live and work in a particular place.
- The Berkman Klein Center identified eight themes among AI principles: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and the promotion of human values.
Frequently Asked Questions
What topics does this course cover?
It covers the governance landscape around AI, AI alignment with human values, external impacts such as environmental effects, deliberate harm and dark patterns, the responsibility of governing bodies, cultural, linguistic, and geographic factors, and an overview of eight ethical AI principle themes identified by the Berkman Klein Center.
What are dark patterns as covered in this course?
Dark patterns are deceptive design patterns used to influence individuals to perform an action that may not be in their best interest.
Which ethical AI principles are reviewed?
The course provides an overview of eight themes identified by the Berkman Klein Center: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and the promotion of human values.
What skills does this course relate to?
It relates to skills including applications of artificial intelligence, artificial intelligence systems, artificial intelligence, data intelligence, environmental intelligence, and intelligent systems.
Transcript
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(bright music) Many organizations already have a governance framework for their information technology or IT. There are many similarities between AI governance and the governance of IT. Let's start with a typical IT governance structure. The International Standards Organization, or ISO. and the International Electro Technical Commission, or IEC, provide the following general framework on the governance of IT. Governing bodies are the ones that assign responsibility for various IT initiatives, given business pressures, regulatory obligations, stakeholder expectations, and business needs. The governing body monitors the performance and conformance of managers, evaluates proposals and plans and directs strategy and policies. This governance framework is focused on the people and processes of the organization to ensure that there is appropriate oversight and accountability. Ultimately, though, it is the governing body of the organization that is accountable to the stakeholders of the organization they're responsible for decisions, actions, and inaction. This includes cases where there's insufficient oversight of an area of the organization. In terms of AI ethics, this means that the governing body is ultimately responsible for ensuring that appropriate policies around AI are in place and followed. They're also responsible for assessing risks involved in IT projects and technology use. But the governance of AI differs from a typical IT governance framework in several ways. AI is more than a simple tool. It adds intelligence to the IT framework and the decision systems it works within. Data collection, cleaning, analysis, and modeling are typically used within an AI system, so the governance of AI should include specific policies, processes and guidelines for data collection, integrity and use in creating an AI system. There should be a framework to ensure the AI systems represent the values of the organization's stakeholders. This includes clarity on the boundaries of customer/supplier accountability. However, none of the specific considerations for AI technology delegates the governance responsibility. It remains with the governing body. In fact, it's critical to of the governing body cannot be delegated.
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