5.2.2 Ethical and Legal Concerns in AI

What is a major ethical concern regarding algorithmic bias in AI systems?

• AI systems are too complex to understand

• AI can make decisions without human intervention

• Algorithmic bias can lead to unfair or discriminatory outcomes

• AI systems are expensive to develop

Who is typically held accountable for decisions made by an AI system?

• The AI system itself

• The end-user of the AI system

• The developers and operators of the AI system

• The data input sources

What is a key legal issue when an autonomous robot causes harm?

• Determining the robot's power source

• Identifying the manufacturer

• Establishing legal liability for the harm caused

• Calculating the robot’s efficiency

What is the concern with "black box" AI models in terms of accountability?

• They require too much processing power

• They make decisions that are difficult to understand or explain

• They are too slow to be practical

• They produce results with 100% accuracy

How can algorithmic bias in AI systems be mitigated?

• By reducing the size of datasets

• By using diverse and representative training data

• By increasing the speed of the AI system

• By allowing AI to self-learn without human intervention

Why is transparency important in AI and machine learning algorithms?

• It speeds up processing times

• It allows stakeholders to understand and trust the AI's decisions

• It reduces the cost of AI development

• It makes the AI immune to hacking

What is the ethical issue surrounding the use of AI in surveillance?

• AI can identify individuals faster

• AI can reduce the need for human surveillance

• AI surveillance can infringe on privacy rights

• AI requires constant monitoring by humans

In the context of robotics, what does 'human-robot interaction safety' refer to?

• The robot’s ability to perform tasks efficiently

• The design of robots to ensure they can operate safely around humans

• The speed at which robots can complete tasks

• The cost-effectiveness of robot production

Why is it important to have diverse teams in AI development?

• To reduce the cost of AI development

• To ensure a variety of perspectives and reduce bias in AI systems

• To speed up the development process

• To make the AI immune to hacking

What is a common challenge in ensuring AI ethics?

• AI systems are too simple to understand

• AI systems require too much processing power

• Ensuring AI systems do not perpetuate existing biases

• AI systems are too slow to be practical