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What is Bias

Handbook of Research on Using Global Collective Intelligence and Creativity to Solve Wicked Problems
A systematic deviation from normative judgement.
Published in Chapter:
Thinking Critically About the Fourth Industrial Revolution as a Wicked Problem
Shaun Ruysenaar (School of Business Leadership, Da Vinci Institute, South Africa)
DOI: 10.4018/978-1-7998-2385-8.ch001
Abstract
This chapter examines the Fourth Industrial Revolution as a wicked problem. By doing so, it promotes critical thinking as a key component required to manage the juggernaut that, in current discourses, has evaded such discussion and possible clarity on plans forward. Not only do the existing frameworks of managing wicked problems provide useful tools to engage with the disruptive technologies and other impacts of the so-called revolution, specific tools relating to critical thinking are explored as fundamental to a beneficial approach though such an approach is one of multiple avenues, possible short-cuts and potential dead ends. In addition, the very context of 4IR suggests a need for ensuring critical thinking as a key transferable skill required to thrive in the changing world, providing a potential catalyst to transform or reignite thinking critically about critical thinking.
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Teen Dating Violence Prevention Based on an Education for Intercultural and Critical Citizenship
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.
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AI and Social Impact: A Review of Current Use Cases and Broader Implications
An attitude and/or stereotype that unconsciously affects a person’s perceptions and actions.
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Overcoming Systemic Racism in Health Professions Advising
Tendency to be for or against something or someone based on preconceived notions.
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Toward the 4th Agenda 2030 Goal: AI Support to Executive Functions for Inclusions
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.
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Inclusion and Accessibility for Students With Disabilities in Higher Education
Social stereotypes about certain groups of people that individuals form outside their own conscious awareness.
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Reinventing Critical Digital Literacy to Empower Student-Teachers in Cross-Cultural, Web-Based Learning Environments
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.
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Applying Machine Learning to Online Data?: Beware! Computational Social Science Requires Care
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.
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Family-Teacher Partnerships to Support Culturally and Linguistically Marginalized Children's Successful Transition to School
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.
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Deep Learning Techniques for Prediction, Detection, and Segmentation of Brain Tumors
An additional parameter used to tune the output along with the weighted sum of the inputs to the neuron.
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Facial Recognition Technology: Ethical and Legal Implications
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).
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Loss Aversion in Companies Whose Location Is Affected by Fire
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.
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Bias and Discrimination in Artificial Intelligence: Emergence and Impact in E-Business
Statistics leading to a distortion that adds an unfair result to a particular group.
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Representation in 21st Century Online Higher Education: How the Online Learning Culture Serves Diverse Students
The implicit or explicit expression and feeling for or against a particular group, especially with regard to race, ethnicity, gender, and other demographic factors.
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Black, White, and Everything in Between: Trials of a Black DEI Professional in PWIs
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.
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A Look at Cognitive Biases Violating Utilitarianism
Biases can be expressed as systematic errors ( Kahneman, 2011 ) or systematic deviations from a normative model ( Baron, 1985 , 2008 , 2012a , 2014a ; Caverni et al., 1990 ).
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The Biased Truth: An Objective Perspective on Nonobjective News Reporting
The distortion, fabrication, or embellishment of information in an effort to slant one’s view in one direction or the other.
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European Initiatives for the Support and Counselling of Victims of Hate Crimes: Key Actors
“The action of unfairly supporting or opposing a particular person or thing because of allowing personal opinions to influence your judgment.” (Cambridge Dictionary)
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Comprehending Algorithmic Bias and Strategies for Fostering Trust in Artificial Intelligence
Bias is an unfair inclination or prejudice in favour of or against something, leading to unbalanced outcomes in various contexts.
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Challenges of a Case Study
A disproportionate prejudice for or against one thing.
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Artificial Intelligence Accountability in Emergent Applications: Explainable and Fair Solutions
Discrimination against a person or a group based with respect to the sensitive data during predictions (supervised learning).
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It's a Team Effort: Collaboration Between Teachers and Professional School Counselors
Prejudicial thoughts or feelings about groups of people, including students with disabilities.
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Some Aspects of Estimators for Variance of Normally Distributed Data
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The Impact of Decentralized Technologies on Social Media Megacorporations
The inclination of the mind or a preconceived opinion about something or someone.
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Leadership and Strategic Decision Making Under Exogenous Shocks Such as COVID-19
Is prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair.
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Critical Considerations for Advancing Gender and Racial Literacies: An Intersectional Approach
This is the unfair privilege and preference shown to one group/individual against another.
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A Matter of Perspective: Discrimination, Bias, and Inequality in AI
Refers to a predisposition, prejudgment or distortion. In law, this often refers to a prejudice, inclination or prejudgment of a question ( Aronson & Groves, 2013 ).
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Culturally Responsive Program Evaluations
Subconscious or conscious predisposition or favoritism.
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Challenges of Developing AI Applications in the Evolving Digital World and Recommendations to Mitigate Such Challenges: A Conceptual View
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.
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Ethical Rationality in AI: On the Prospect of Becoming a Full Ethical Agent
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.
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Digital Storytelling: A Student-Centered Approach for Shifting the School Discipline Narrative Using Story, Technology, and Data as Interventions
A misaligned personal assumption about an external situation, group, or person that conflicts with the truth or reality about that situation, group or person.
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Cultural Considerations to Enhance Student Success
A tendency to believe that some people, ideas, etc., are better than others that usually results in treating some people unfairly.
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African American Women Leaders: Leadership Requires Courage, Collaboration, Communication, and Commitment
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.
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Mitigation of Test Bias in International, Cross-National Assessments of Higher-Order Thinking Skills
Any systematic differences in the meaning of test scores that are associated with group membership.
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