4.Artificial Intelligence Fundamentals

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What is a foundational consideration when assessing the fairness of a decision?

Evaluating the simplicity of the decision-making process

Calculating the financial success of the decision

Identifying any disproportionate impact on individuals or groups (correct)

Understanding the impact on the largest number of people

What might characterize a 'good bias' in decision-making?

Focusing on the majority while dismissing minority demographics

Targeting marketing efforts based on incomplete data

Providing relevant advertisements to a well-defined audience (correct)

Exclusively promoting products to a specific demographic

Which of the following is NOT suggested as a way for leaders to create an ethical culture?

Establishing processes aligned with values

Encouraging competition among employees (correct)

Clearly defining core values

Rewarding ethical behaviors

Due to systemic biases, which group is mentioned as potentially receiving unfair assessments?

Non-binary and transgender individuals Signup and view all the answers

What must leaders do to prevent the spread of unethical behavior in a company?

Define core values and reward ethical behavior Signup and view all the answers

What is a potential consequence of failing to incorporate diverse identities in marketing?

Exclusion of individuals who could benefit from the product Signup and view all the answers

What is an essential action for individuals working in ethical domains?

Actively question and improve ethical practices Signup and view all the answers

Which of the following best defines the challenge of fairness in decision-making?

The complexity of assessing potential unfair impacts accurately Signup and view all the answers

What does confirmation bias primarily influence in recommendation systems?

The shaping of preconceived notions about a product Signup and view all the answers

What was a critical flaw in the AI used for the 2016 beauty contest?

It was not trained on a diverse set of beauty standards. Signup and view all the answers

How did Shirley cards affect the development of color photography?

They standardized color balancing based on a white model. Signup and view all the answers

What does societal bias imply in data algorithms?

It reflects historical prejudices against marginalized communities. Signup and view all the answers

What was the purpose of redlining in the 1930s?

To color-code neighborhoods based on perceived risk for loans. Signup and view all the answers

Which of the following best describes automation bias?

The inclination to prefer machine-generated values over personal ones. Signup and view all the answers

What issue arose from Kodak's use of Shirley cards in photography?

They reinforced a narrow definition of beauty linked to fair skin. Signup and view all the answers

What is a potential consequence of incorporating zip codes into data algorithms?

It could inadvertently factor in race when making decisions. Signup and view all the answers

What is the primary purpose of creating a clear, anonymous process for employees to submit ethical concerns?

To reinforce an ethical culture and empower employees to speak up. Signup and view all the answers

Why are checklists recommended in building an ethical culture?

They provide a consistent and easy-to-implement resource. Signup and view all the answers

What should be documented to support transparency and consistency in ethical decision-making?

The decisions made at ethical crossroads and their rationales. Signup and view all the answers

How can understanding customer needs help in ethical decision-making?

It identifies potential harm and misuse of products. Signup and view all the answers

What is the key responsibility associated with the use of artificial intelligence according to the content provided?

Providing access to AI benefits for everyone and ensuring safe use. Signup and view all the answers

What potential risks must be considered when designing products for customers?

Assumptions made about needs without customer consultation. Signup and view all the answers

What aspect of AI ensures that it can benefit all stakeholders involved?

The commitment to ethical training for users and creators. Signup and view all the answers

What is mentioned as a consideration when evaluating customer understanding in product design?

The potential negative use of products by bad actors. Signup and view all the answers

What is a primary cause of survival or survivorship bias in hiring practices?

Evaluating only current employees and not considering those let go. Signup and view all the answers

How can interaction bias be created when interacting with AI systems?

By deliberately teaching AI systems incorrect behaviors or data. Signup and view all the answers

Which factor contributes to bias entering an AI system prior to its deployment?

Subjective assumptions made by its creators before building the system. Signup and view all the answers

What is a potential issue when AI models are trained using biased training data?

They will generate recommendations consistent with historical hiring patterns. Signup and view all the answers

What should be done to limit the influence of assumptions in AI system design?

Encourage diversity in teams involved in AI research and design. Signup and view all the answers

Which type of data can serve as a proxy for race, gender, or age in AI training?

Zip codes and geographic locations. Signup and view all the answers

What can result from using protected categories like age, race, or gender in financial decision-making?

Legal consequences for organizations. Signup and view all the answers

Why is it problematic for AI systems to focus solely on data from successful candidates?

It can overshadow the potential of excluded candidates. Signup and view all the answers

How can unintended biases in AI systems be addressed effectively?

Through community engagement and allowing users to opt out or correct their data. Signup and view all the answers

What should be a primary consideration in the development of ethical AI systems?

How data from different cultural contexts may affect algorithm outputs. Signup and view all the answers

What is a key consideration when generating images for projects using AI?

Art is subjective, and perfection is not necessary. Signup and view all the answers

What can lead to a narrow focus while generating art with AI?

Shifting the goal to finding a perfect image. Signup and view all the answers

What role do community review processes play in AI system development?

They enable correction of oversights by including impacted community perspectives. Signup and view all the answers

How does flexibility benefit the process of generating images with AI?

It can result in faster and potentially cheaper outcomes. Signup and view all the answers

Why is it important to evaluate the training data used in AI systems?

To identify and mitigate unrecognized biases that may affect outcomes. Signup and view all the answers

What is a potential consequence of algorithms that do not adapt to changing cultural values?

They may produce outputs that are irrelevant or offensive to communities. Signup and view all the answers

What does prompt engineering primarily involve?

Experimenting with prompts to understand AI responses. Signup and view all the answers

What should be the primary goal when using imagery in projects?

To enhance the content and break up text effectively. Signup and view all the answers

What underlying aspect is crucial for realizing socially beneficial AI?

Awareness of the human impact and representation during development. Signup and view all the answers

What aspect of art creation with generative AI is often debated among artists?

The definition and structure of good prompts. Signup and view all the answers

Which factor significantly influences the outcomes of AI systems during development?

The cultural and demographic diversity of the development team. Signup and view all the answers

Why might an artist settle for an image that is not flawless?

Perfection is often unnecessary for the project's purpose. Signup and view all the answers

What is a key challenge faced by algorithm developers in relation to data interaction?

Anticipating and managing the interactions between various datasets and models. Signup and view all the answers

In the context of using AI for image creation, what does being 'smart' imply?

Understanding the balance between flexibility and focus. Signup and view all the answers

Study Notes

Responsible Creation of Artificial Intelligence

Emerging technology is impacting society in various ways, including automation replacing jobs and the developmental effects of social media.
Many industries have established standards, protocols, and regulations to ensure ethical practices (e.g., Hippocratic Oath in medicine, driving laws in the automobile industry).
The UN's 2011 Guiding Principles for Business and Human Rights defines responsibilities for businesses and states.
Salesforce has an Office of Ethical and Humane Use promoting positive societal impact and anchored in their core values.
Bias in technology is defined as systematic and repeatable errors in a computer system that create unfair outcomes.
Bias can be caused by inaccurate assumptions in the machine learning process, systematic deviations from the truth, or societal and legal prejudices.
Not all bias is bad; some companies may target only men in their advertising when appropriate (e.g., prostate cancer drugs).

Ethical Culture

Most companies don't intend to cause harm.
Establishing clear values, processes, and incentives is important for an effective ethical company culture.
Good leadership emphasizes ethical behavior and addresses unethical behavior promptly.
Diverse teams, clear processes, and detailed understanding of customers are components of a solid organizational ethical culture.

Build Diverse Teams

Research shows that diverse teams are more creative and hardworking.
Companies should strive for diversity in teams (experience, age, race, ability).
Lack of diversity can result in biased products and features.
Teams should include people from underrepresented groups.
Employees should feel comfortable challenging and speaking up about ethical aspects of workplace projects

Translate Values into Processes

Every organization has a set of values that guide decision-making.
Incentive structures can reward behaviors aligned with values.
Resources and documentation can provide further clarity or support employees.

Understand Your Customers

Understanding customer needs and values is fundamental to designing effective technology.
Consider who is at risk and why.
Evaluate whether existing algorithms can perpetuate existing biases.

Recognize Bias in Artificial Intelligence

Al should be accessible to all.
It's important to understand how Al systems can maintain accuracy and fairness (avoiding bias) in their functions.
Al should not reproduce societal biases.
Al creates an ethical dilemma as to how to judge whether the biases introduced by Al are "good" bias, "bad" bias, or neutral bias.

What is Ethical vs. Legal

Laws exist to govern societal behaviors from citizens, but ethical considerations can extend beyond the law (e.g., US law protecting protected class information).
Al can be designed to be fairer than current methods of human judgment, particularly when assessing for bias.
It is important to consider whether Al models are promoting or respecting human rights.

Types of Bias

Measurement bias occurs when data is incorrectly labeled, categorized, or oversimplified.
Association bias labels based on preconceived ideas.
Confirmation bias labels data based on preconceived ideas.
Automation bias imposes a system's values on others.
Societal bias reproduces past prejudice toward marginalized groups.

Survival or Survivorship Bias

Al evaluation may only include the successful results and ignore those that were excluded.
Consider all results, both positive and negative, in a system or process when evaluating it

Interaction Bias

Human interaction can intentionally influence or introduce bias into AI systems or models.
Bias can occur through intentional or unintentional actions.
Understand potential human impact on data and results

How Does Bias Enter the System

Al models can inherit biases from the data they're trained on.
The data that trains the Al model should be comprehensive (avoiding missing or incomplete data).
Social context may also introduce bias into the model

Training Data

Al model training data may reflect existing biases (e.g., gender or race).
The quality of data used to train an AI model, including possible overrepresentation or underrepresentation of values and traits

Human Intervention or Lack Thereof

Training data can be modified (edited directly or excluded).
Different groups may require different models or algorithms.

Al Can Magnify Bias

Training AI models on biased data amplifies those biases.
There are several different types of bias that impact AI systems and models.
Evaluation and assessments of AI models must be performed to mitigate bias

Remove Bias from Algorithms and Your Data

Bias prevention begins with data management, planning, and execution.
Review the project premortem to identify factors and potential ethical concerns.
Recognize possible excluded or overrepresented factors from training data, and evaluate its impact
Use multiple or modified algorithms when needed for specific groups or criteria.

How to Create Responsible Al: Use Checks and Balances

Trust in Al models requires that models are trained responsibly.
Policies and procedures should be placed on how to train and test models.
Ethical considerations for Al models and systems must be carefully evaluated.

Generative Al for Images

Generative Al can efficiently produce text-based outputs, 3D objects, and animations.
Diffusion models are used for creating images and animations, they work by "dispersing" the image into a smaller and more manageable set of data, and then recreate the "lost" pieces, similar to an "un-scrambling" process.
Different tools are available and can be used for different purposes (e.g., fine-tuning, creativity, and other needs).

Using Generative Al For Effective and Responsible Art

Generative Al models may be used for presentations and projects in many fields, to enhance visual appeal and clarity.
Generative Al models have their own strengths and weaknesses in art. Artists must be realistic and recognize the limits of generative models.
Generative Al is not a replacement for artists, but a tool that can help artists achieve desired outcomes efficiently.

Ethics of Generated Artwork

The rise of Generative AI has brought with it ethical concerns, including concerns about plagiarism and impersonation.
Important to understand how the AI model was trained and assure safety.
Transparency in how Al is used is critical.
It's important to acknowledge and mitigate possible negative impacts (e.g., creating falsified content or imagery).

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.