What is Bias

1.

A systematic deviation from normative judgement. Learn more in: Thinking Critically About the Fourth Industrial Revolution as a Wicked Problem

2.

Bias refers to the way our past experiences distort our perception and reaction to information unfairly. People can develop biases towards or against an individual, an ethnic group, a sexual or gender identity, a nation, a religion, a social class, a political party, paradigms and theoretical ideologies within academic domains or species. This is why some people use the word “bias” as a synonym for prejudice. Learn more in: Teen Dating Violence Prevention Based on an Education for Intercultural and Critical Citizenship

3.

An attitude and/or stereotype that unconsciously affects a person’s perceptions and actions. Learn more in: AI and Social Impact: A Review of Current Use Cases and Broader Implications

4.

Tendency to be for or against something or someone based on preconceived notions. Learn more in: Overcoming Systemic Racism in Health Professions Advising

5.

Machine learning bias, also sometimes called algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process. Learn more in: Toward the 4th Agenda 2030 Goal: AI Support to Executive Functions for Inclusions

6.

Social stereotypes about certain groups of people that individuals form outside their own conscious awareness. Learn more in: Inclusion and Accessibility for Students With Disabilities in Higher Education

7.

Prejudice in favor or against. Learn more in: The Impact of Human Behavior on Cyber Security

8.

Incline towards or be prejudice in favor of or against an individual, an event, other’s points of view, etc. that may be deemed unfair and unjust. Learn more in: Reinventing Critical Digital Literacy to Empower Student-Teachers in Cross-Cultural, Web-Based Learning Environments

9.

Prejudice towards or against a person, a group, or a class. In a machine learning context, there are various types of biases. Each bias can affect a model differently. Learn more in: Applying Machine Learning to Online Data?: Beware! Computational Social Science Requires Care

10.

The negative evaluation of one group and its members relative to another (Blair, Steiner, & Havranek, 2011). Learn more in: How an Anti-Racist Organizational Change Model Can Build Capacity to Support Historically Excluded Students: A Guide for Advisors and Administrators of Pathway Programs

11.

Arbitrary and often baseless belief about something. Learn more in: The Cultural Impact of Hidden Curriculum on Language Learners: A Review and Some Implications for Curriculum Design

12.

Prejudice against or in favor of a particular social group, individual, or belief. While all humans exhibit biases, biases can lead to unjust actions. This is particularly problematic when those unjust actions are carried out by people in power. Learn more in: Family-Teacher Partnerships to Support Culturally and Linguistically Marginalized Children's Successful Transition to School

13.

Discriminatory treatment for or against another in a way that seems unfair. Learn more in: Navigating Inequitable (Mis)Treatment and Racist Harassment in Higher Education During the COVID-19 Pandemic: A Self-Decentered Autoethnographic Case

14.

An additional parameter used to tune the output along with the weighted sum of the inputs to the neuron. Learn more in: Deep Learning Techniques for Prediction, Detection, and Segmentation of Brain Tumors

15.

In this particular paper, a bias is a personal inclination towards making a prejudiced or unfair judgment against something, someone, or a group (Merriam-Webster, n.d.a). Learn more in: Facial Recognition Technology: Ethical and Legal Implications

16.

A disproportionate weight in favor of or against an idea or thing. Biases can be innate or learned. Can be closed-minded, prejudicial, or unfair. People may develop biases for or against an individual, a group, or a belief. Learn more in: Loss Aversion in Companies Whose Location Is Affected by Fire

17.

Statistics leading to a distortion that adds an unfair result to a particular group. Learn more in: Bias and Discrimination in Artificial Intelligence: Emergence and Impact in E-Business

18.

The implicit or explicit expression and feeling for or against a particular group, especially with regard to race, ethnicity, gender, and other demographic factors. Learn more in: Representation in 21st Century Online Higher Education: How the Online Learning Culture Serves Diverse Students

19.

Prejudicial leaning, treatment, or action that is for, in favor of, or against a person or group based on their perceived membership in a particular group such as race or gender. It is perceived as negative and unfair treatment or judgement. Learn more in: Black, White, and Everything in Between: Trials of a Black DEI Professional in PWIs

20.

The distortion, fabrication, or embellishment of information in an effort to slant one’s view in one direction or the other. Learn more in: The Biased Truth: An Objective Perspective on Nonobjective News Reporting

21.

A disproportionate prejudice for or against one thing. Learn more in: Challenges of a Case Study

22.

Discrimination against a person or a group based with respect to the sensitive data during predictions (supervised learning). Learn more in: Artificial Intelligence Accountability in Emergent Applications: Explainable and Fair Solutions

23.

Prejudicial thoughts or feelings about groups of people, including students with disabilities. Learn more in: It's a Team Effort: Collaboration Between Teachers and Professional School Counselors

24.

The bias of an estimator T of the parameter ? is defined as: . Learn more in: Some Aspects of Estimators for Variance of Normally Distributed Data

25.

The inclination of the mind or a preconceived opinion about something or someone. Learn more in: The Impact of Decentralized Technologies on Social Media Megacorporations

26.

Is prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair. Learn more in: Leadership and Strategic Decision Making Under Exogenous Shocks Such as COVID-19

27.

This is the unfair privilege and preference shown to one group/individual against another. Learn more in: Critical Considerations for Advancing Gender and Racial Literacies: An Intersectional Approach

28.

Refers to a predisposition, prejudgment or distortion. In law, this often refers to a prejudice, inclination or prejudgment of a question ( Aronson & Groves, 2013 ). Learn more in: A Matter of Perspective: Discrimination, Bias, and Inequality in AI

29.

Subconscious or conscious predisposition or favoritism. Learn more in: Culturally Responsive Program Evaluations

30.

Here bias refers to the prejudice or inclination of choice to one aspect of the decision. In AI bias refers to the prediction being made always in favour of the data set already the system has been trained with. Learn more in: Challenges of Developing AI Applications in the Evolving Digital World and Recommendations to Mitigate Such Challenges: A Conceptual View

31.

Can be positive or negative. Learn more in: Reflexivity in the Resistance to Enterprise Resource Planning (ERP) Innovation

32.

Attitude comparable to a form of prejudice which may be built into certain ways of thinking or may pertain to the way in which data is treated. Learn more in: Ethical Rationality in AI: On the Prospect of Becoming a Full Ethical Agent

33.

A misaligned personal assumption about an external situation, group, or person that conflicts with the truth or reality about that situation, group or person. Learn more in: Digital Storytelling: A Student-Centered Approach for Shifting the School Discipline Narrative Using Story, Technology, and Data as Interventions

34.

Prejudiced against someone or something for a particular reason. Learn more in: Teaching Across the Demographic Divide With Latinx Texts on Immigration

35.

A tendency to believe that some people, ideas, etc., are better than others that usually results in treating some people unfairly. Learn more in: Cultural Considerations to Enhance Student Success

36.

The disproportionate weight in favor of or against an idea or thing, usually in a way that is prejudicial or unfair. Biases can be innate or learned. For example, people may develop preferences for or against an individual, a group, or a belief. Learn more in: African American Women Leaders: Leadership Requires Courage, Collaboration, Communication, and Commitment

37.

Any systematic differences in the meaning of test scores that are associated with group membership. Learn more in: Mitigation of Test Bias in International, Cross-National Assessments of Higher-Order Thinking Skills