Home AI Courses AI: Ethics & Societal Challenges

AI: Ethics & Societal Challenges

(0 reviews)

A four-week course that explores the ethical and societal implications of artificial intelligence, addressing topics such as AI bias, surveillance, democracy, consciousness, responsibility, and control, and fostering reflection and discussion on these issues.

Key AI Functions:Ethics Of Artificial Intelligence,Data Science,Governance and society

Description

Reviews

Alternative Tools

Description for AI: Ethics & Societal Challenges

Gain an understanding of the ethical and societal ramifications of AI, such as its influence on democracy, algorithmic bias, and surveillance.

Develop an understanding of the intricacies of consciousness and intelligence, and investigate methods for the creation of artificial consciousness.

Discover the concepts of accountability in autonomous systems and safe AI development, as well as the concepts of responsibility and control in AI.

Develop the capacity to engage in discussions and contemplate the ethical and societal implications of AI, with a fundamental comprehension of AI bias, democracy, intelligence, consciousness, and control issues.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 21

Offered by: On Coursera provided by Lund University

Duration: 3 weeks at 4 hours a week

Schedule: Flexible

Reviews for AI: Ethics & Societal Challenges

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

Bias and Discrimination in AI

ML with Spark on Google Cloud Dataproc

ML & Reinforcement Learning in Finance Specialization

Foundations of Data Science: K-Means Clustering in Python

Supporting Vector Machines in Python, From Start to Finish

Alternative Tools for AI: Ethics & Societal Challenges

NovaceneAI

Freemium

NovaceneAI streamlines the organization of unstructured text data with AI algorithms, offering dedicated cloud hosting, adaptability across sectors, and robust data privacy measures.

#research #automation

Posit

Paid

Posit offers a comprehensive platform with enterprise solutions, cloud applications, community resources, and deployment solutions to enhance productivity in data science teams.

#project management # library

Gen AI Assisting Data Scientists

Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.

#Artificial Intelligence (AI) #Data Science

Gen AI: Elevate Your Data Science Career

Learn to use generative AI tools to improve data science workflows, enhance datasets, and refine machine learning models through practical projects.

#Data Science #Data Analysis

AI in Efficient Programming: Harnessing the Power of LLMs

Gain a comprehensive understanding of AI's potential, ethical considerations, and applications in efficient programming and common coding tasks using various LLMs.

#Ethics Of Artificial Intelligence #Data Science

Python: Data Science, AI & Development

Master Python programming for software development and data science, including core logic, Jupyter Notebooks, libraries like NumPy and Pandas, and web data gathering with Beautiful Soup and APIs.

#Data Science #Data Analysis

Artificial Intelligence (AI) - An Introductory Course

Understand AI, its applications, concepts, ethical concerns, and receive expert career guidance.

#Artificial Intelligence (AI) #Data Science

AI Accessible to Everyone

Gain a comprehensive understanding of AI terminology, applications, development, and strategy, while navigating ethical and societal considerations in a non-technical context.

#Machine Learning projects #AI terminology

IBM Data Science Professional Certificate

Prepare for a vocation as a data scientist. Acquire hands-on experience and in-demand skills to become job-ready in as little as five months. No prior experience is necessary.

#Data Science #Big Data

Investment Management with Python and ML Specialization

Learn to create and diversify portfolio strategies, apply machine learning to financial data, and utilize quantitative modeling and data analytics for investment decisions.

#Risk Management #Portfolio construction and analysis