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Algorithmic Bias: Policy Implications and Solutions
Explore algorithmic bias, its societal impact, and develop strategies to address this critical policy issue.
Course Cost
Free course
Intermediate
Skill Level
7 Hours
Self-paced lessons
This Teach-Out course examines algorithmic bias as a pressing policy concern, providing policymakers and leaders with essential knowledge to navigate this complex issue. The course defines algorithms and algorithmic bias, explores their widespread use in various sectors, and investigates the sources and impacts of bias. Participants will learn to identify algorithms in use, understand how bias manifests, and recognize the connections between algorithmic bias and systemic discrimination. The course emphasizes practical approaches to mitigate bias, encouraging learners to develop strategies for addressing this issue in their professional contexts. By the end, participants will be equipped to engage in informed discussions about algorithmic bias, raise awareness of its implications, and take concrete steps to reduce its impact on communities they serve.
What you'll learn
Understand what algorithms are and how they are used in various policy areas
Identify sources and manifestations of algorithmic bias
Recognize connections between algorithmic bias and systemic discrimination
Develop strategies to address and mitigate algorithmic bias
Learn to communicate effectively about algorithmic bias issues
Understand the policy implications of algorithmic decision-making
Explore ethical considerations in the development and use of algorithms
Develop skills to advocate for fairness and equity in algorithmic systems
Skills you'll gain
This course includes:
3.5 Hours PreRecorded video
1 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 5 modules in this course
This Teach-Out course explores algorithmic bias as a critical policy issue, designed for policymakers, agency leaders, and professionals in related fields. The curriculum is divided into five modules, covering the fundamentals of algorithms, the nature and sources of algorithmic bias, its relationship to systemic bias, and strategies for addressing this issue. Participants learn to identify algorithms in use, understand how bias manifests in algorithmic systems, and recognize the broader societal implications of algorithmic decision-making. The course emphasizes practical approaches to mitigating bias, including participatory methods in algorithm development, addressing bias at various stages of the algorithmic lifecycle, and strategies for raising awareness and initiating change within organizations. Throughout the course, learners engage with real-world examples, expert insights, and interactive activities to deepen their understanding and develop actionable strategies for their professional contexts.
Welcome to the Course
Module 1 · 6 Minutes to complete
What is an Algorithm?
Module 2 · 2 Hours to complete
What Does It Mean for an Algorithm To Be Biased?
Module 3 · 2 Hours to complete
Algorithmic Bias and Systemic Bias
Module 4 · 1 Hours to complete
Anticipating and Addressing Algorithmic Bias
Module 5 · 2 Hours to complete
Fee Structure
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
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Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.