ISQS - Artificial Intelligence and Machine Learning

What are the key challenges that needs to be addressed to create a health AI ecosystem?

1. Bias built into data 2. AI - induced bias 3. teaching AI human rules 4. evaluating cases of suspecting AI bias

IBM Watson System

Watson builds up evidence for the answers it finds by looking at thousands of pieces of text that give it a level of confidence in its conclusion, combines the ability to recognize patterns in text with the very different ability to weigh the evidence that matching those patterns provides - informed or inspired by human reasoning

IBM's Deep Blue System

a system that was a master chess player, but certainly did not play in the same way that humans do

Define Strong AI

any result can be used to not only build systems that think but also to explain how humans think as well

AI-Induced Biases

biases can be created with AI systems and then become amplified as the algorithms evolve, they learn and change over time

What is artificial intelligence a sub-field of?

computer science

Narrow AI

created to solve one given problem

Data Biases

data give AI sustenance, including its ability to learn at rates far faster than human, the data that AI systems use as input can have build in biases, despite the best efforts of AI programmers

What is the overarching goal of AI?

enable the development of computers that are able to do things normally done by people in particular, things associated with people acting intelligent

How many jobs may be automated by machines?

one in every two jobs have a high risk

General AI

solving any problem that require AI

Define In-Between-AI

systems that are informed or inspired by human reasoning

Define Weak AI

while we might be able to build systems that can behave like humans, the results will tell us nothing about how humans think