Imagine the following situation: Discussion at University
Individual Long Turn 4-5 min
You study at the University of Natural Resources and Life Science, Vienna (BOKU) and you want to get to know students from abroad. So you organise discussion night. For your international colleagues you introduce your topic before the discussion.
- How can we ensure that AI systems are transparent and accountable?
- What measures can be taken to prevent AI from perpetuating or amplifying biases?
- How can privacy be protected in the age of AI?
- What are the potential societal impacts of widespread AI adoption, particularly on employment?
Paired Activity 8-10 min.
After you take some drinks with your colleagues. There you converse about:
- How can we address the ethical implications of AI in autonomous systems, such as self-driving cars and drones?
- What are the risks associated with the development of superintelligent AI, and how can they be mitigated?
- How can international cooperation be fostered to regulate and manage the development and use of AI?
- What is artificial intelligence (AI)?
- Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. These systems can perform tasks such as visual perception, speech recognition, decision-making, and language translation.
- What are the main types of AI?
- The main types of AI are:
- Narrow AI (Weak AI): Designed and trained for a specific task, such as voice assistants (e.g., Siri, Alexa).
- General AI (Strong AI): Has generalized human cognitive abilities and can learn to perform various tasks.
- Superintelligent AI: An AI that surpasses human intelligence and capability in all aspects.
- What is machine learning, and how does it relate to AI?
- Machine learning is a subset of AI that involves the use of algorithms and statistical models to enable computers to improve their performance on a task through experience. It allows systems to learn from data rather than being explicitly programmed.
- What are neural networks, and why are they important in AI?
- Neural networks are a series of algorithms that attempt to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. They are fundamental in deep learning, a subset of machine learning, which is crucial for tasks such as image and speech recognition.
- How is AI being used in healthcare?
- In healthcare, AI is used for various applications, including diagnosing diseases, predicting patient outcomes, personalized treatment plans, drug discovery, and managing medical records. AI algorithms can analyze complex medical data and provide insights that help improve patient care.
- What are the ethical concerns associated with AI?
- Ethical concerns associated with AI include issues of privacy, bias, accountability, and the potential for job displacement. There are also concerns about the misuse of AI in surveillance, autonomous weapons, and the long-term impact on human society and behavior.
- What is the Turing Test, and what does it measure?
- The Turing Test, proposed by Alan Turing, is a measure of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. If a machine can engage in a conversation with a human without being detected as a machine, it is said to have passed the Turing Test.
- What are the future trends in AI research and development?
- Future trends in AI research and development include:
- Advancements in natural language processing (NLP): Improving machines' ability to understand and generate human language.
- AI in autonomous vehicles: Enhancing the safety and efficiency of self-driving cars.
- AI in robotics: Developing more sophisticated robots for various applications, from manufacturing to personal assistants.
- Ethical AI: Creating frameworks and guidelines to ensure the responsible use of AI.
- General AI: Researching the possibility of creating AI with generalized human-like intelligence.Chat
ChatGPT Mai/2024
