bad decision bias 2 5 6
play

bad decision bias? 2 5 6 Affinity Bias: What can we do? 2. - PowerPoint PPT Presentation

Feb 26, 2024 •141 likes •292 views

bad decision bias? 2 5 6 Affinity Bias: What can we do? 2. 3. 1. Seek outputs Compare rather than Be aware performance compentenci not people es 7 9 10 11 12 Unconscious bias refers to a

  1. bad 
 decision 
 bias?

  2. � 2

  5. � 5

  6. � 6

  7. Affinity Bias: 
 What can we do? 2. 3. 1. Seek outputs Compare rather than Be aware performance compentenci not people es � 7

  9. � 9

  10. � 10

  11. � 11

  12. � 12

  13. “ Unconscious bias refers to a bias that we are unaware of, and which happens outside of our control. It is a bias that happens automatically and is triggered by our brain making quick judgments and assessments of people and situations, influenced by our background, cultural environment and personal experiences (ECU: 2013 Unconscious bias in higher education) � 13

  14. Recap Representation ▪ Name blind applications ▪ Pre-interview prompts Affinity Bias ▪ Outputs not competencies Framing / Status Quo Bias ▪ Encourage good decisions with good questions and prompts � 14

  15. � 15

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

CSC 311: Introduction to Machine Learning Lecture 5 - Decision Trees & Bias-Variance

CSC 311: Introduction to Machine Learning Lecture 5 - Decision Trees & Bias-Variance

CSC 311: Introduction to Machine Learning Lecture 5 - Decision Trees & Bias-Variance Decomposition Roger Grosse Chris Maddison Juhan Bae Silviu Pitis University of Toronto, Fall 2020 Intro ML (UofT) CSC311-Lec5 1 / 49 Today Decision

1.49k views • 50 slides
Learning Decision Trees Representation is a decision tree. Bias is towards simple decision

Learning Decision Trees Representation is a decision tree. Bias is towards simple decision

Learning Decision Trees Representation is a decision tree. Bias is towards simple decision trees. Search through the space of decision trees, from simple decision trees to more complex ones. Decision trees A decision tree is

484 views • 10 slides
BIAS What Is Bias? Bias can be defined as favoring one side, position, or belief being

BIAS What Is Bias? Bias can be defined as favoring one side, position, or belief being

BIAS What Is Bias? Bias can be defined as favoring one side, position, or belief being partial or prejudiced Where have you seen bias? Bias vs. Propaganda Bias is prejudice; a preconceived judgment or an opinion formed

717 views • 29 slides
Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams Laura I. Galindez

Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams Laura I. Galindez

Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams Laura I. Galindez Olascoaga , Wannes Meert , Nimish Shah , Guy Van den Broeck , Marian Verhelst Outline Motivation and objective Background

397 views • 29 slides
Equity & Excellence: Hidden Bias Implicit Bias Inherent Bias

Equity & Excellence: Hidden Bias Implicit Bias Inherent Bias

Equity & Excellence: Hidden Bias Implicit Bias Inherent Bias ____________________________________________ Vincent R. De Lucia Educator-in-Residence Director of Mandatory Training & PD New Jersey School Boards Association Anderson

426 views • 41 slides
Decision Tree R Greiner Cmput 466 / 551 Learning Decision Trees Def'n: Decision Trees

Decision Tree R Greiner Cmput 466 / 551 Learning Decision Trees Def'n: Decision Trees

HTF: 9.2 B: 14.4 R N , C h a p t e r 1 8 1 8 . 3 Decision Tree R Greiner Cmput 466 / 551 Learning Decision Trees Def'n: Decision Trees Algorithm for Learning Decision Trees Entropy, Inductive Bias (Occam's

1.43k views • 87 slides
Adversary presentation and bias in legal decision making Article in Harvard Law Review December

Adversary presentation and bias in legal decision making Article in Harvard Law Review December

See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/258440342 Adversary presentation and bias in legal decision making Article in Harvard Law Review December 1972 CITATIONS READS 6 94

634 views • 18 slides
10701 Machine Learning Boosting Fighting the bias-variance tradeoff Simple (a.k.a. weak)

10701 Machine Learning Boosting Fighting the bias-variance tradeoff Simple (a.k.a. weak)

10701 Machine Learning Boosting Fighting the bias-variance tradeoff Simple (a.k.a. weak) learners are good e.g., nave Bayes, logistic regression, decision stumps (or shallow decision trees) Low variance, dont usually overfit

686 views • 31 slides
Bias-Variance Tradeoff Machine Learning 1 Bias and variance Every learning algorithm requires

Bias-Variance Tradeoff Machine Learning 1 Bias and variance Every learning algorithm requires

Bias-Variance Tradeoff Machine Learning 1 Bias and variance Every learning algorithm requires assumptions about the hypothesis space. Eg: My hypothesis space is linear decision trees with 5 nodes a three layer

189 views • 17 slides
BIAS BIAS LIGHT LIGHT & & MEDIUM MEDIUM TR TRUCK UCK TIRES TIRES Bias Bias Ligh

BIAS BIAS LIGHT LIGHT & & MEDIUM MEDIUM TR TRUCK UCK TIRES TIRES Bias Bias Ligh

BIAS BIAS LIGHT LIGHT & & MEDIUM MEDIUM TR TRUCK UCK TIRES TIRES Bias Bias Ligh ight T t Truck / / Trail iler r Ti Tire Si Size No Nome mencla latu ture 9.50-16 9.50 16.5L .5LT/D T/D ST ST 7.00 7.00-15 15 1 10

121 views • 11 slides
Bias in, Bias out: Gender Equality and the Fourth Industrial Revolution Debra Howcroft and

Bias in, Bias out: Gender Equality and the Fourth Industrial Revolution Debra Howcroft and

Bias in, Bias out: Gender Equality and the Fourth Industrial Revolution Debra Howcroft and Jill Rubery Work and Equalities Institute University of Manchester Bias in, bias out: an overview Two parts Identify the methodology

706 views • 21 slides
Decision-making Bias in Instance Matching Model Selection Mayank Kejriwal, Daniel P . Miranker

Decision-making Bias in Instance Matching Model Selection Mayank Kejriwal, Daniel P . Miranker

Decision-making Bias in Instance Matching Model Selection Mayank Kejriwal, Daniel P . Miranker Acknowledgements: US National Science Foundation, Microsoft Research Instance Matching 50+ year old Artificial Intelligence problem When do

231 views • 19 slides
Expectancy bias and Bias and forensic evidence Bias and speech research forensic speech

Expectancy bias and Bias and forensic evidence Bias and speech research forensic speech

Overview Bias effects Expectancy bias and Bias and forensic evidence Bias and speech research forensic speech research Blind forensic speech research Maartje Schreuder TMFI / Maastricht University I AFPA 2011 Bundeskrim

180 views • 7 slides
Implicit Bias Implicit bias Implicit bias refers to attitudes or stereotypes that affect our

Implicit Bias Implicit bias Implicit bias refers to attitudes or stereotypes that affect our

Implicit Bias Implicit bias Implicit bias refers to attitudes or stereotypes that affect our understanding, actions and decisions in an unconscious manner. It's different from suppressed thoughts we might conceal to keep the peace; it's

634 views • 16 slides
> b x 2 w 3 x 3 Neuroscience 101 CMPSCI 689 Subhransu Maji (UMASS) 3 /19 CMPSCI 689

> b x 2 w 3 x 3 Neuroscience 101 CMPSCI 689 Subhransu Maji (UMASS) 3 /19 CMPSCI 689

So far in the class Decision trees ! Inductive bias: use a combination of small number of features ! Nearest neighbor classifier ! Perceptron Inductive bias: all features are equally good Perceptrons Today ! Subhransu Maji

565 views • 7 slides
Bias Busting Across the Center: A Model to Interrupt Bias and Promote Inclusion Modeled on

Bias Busting Across the Center: A Model to Interrupt Bias and Promote Inclusion Modeled on

Bias Busting Across the Center: A Model to Interrupt Bias and Promote Inclusion Modeled on Googles BiasBusting@Work and Carnegie Mellons Bias Busters @ CMU Learning Outcomes Understand the role that biases play, positively &

637 views • 34 slides
UNCONSCIOUS BIAS JOY WARMINGTON, CEO brap, The Arch, First Floor, 48-52 Floodgate Street,

UNCONSCIOUS BIAS JOY WARMINGTON, CEO brap, The Arch, First Floor, 48-52 Floodgate Street,

WAKING UP TO UNCONSCIOUS BIAS JOY WARMINGTON, CEO brap, The Arch, First Floor, 48-52 Floodgate Street, Birmingham B5 5SL Email: brap@brap.org.uk | Telephone: 0121 272 8450 Twitter: @braphumanrights | Facebook: brap.human.rights WWW.BRAP.ORG.UK

417 views • 8 slides
The impact of ocean sound speed variability on the uncertainty of geoacoustic parameter estimates

The impact of ocean sound speed variability on the uncertainty of geoacoustic parameter estimates

The impact of ocean sound speed variability on the uncertainty of geoacoustic parameter estimates N. Ross Chapman and Yong-Min Jiang University of Victoria Victoria BC Canada University of Victoria, Victoria, BC, Canada Work supported by

354 views • 18 slides
Inflation Uncertainty - Survey Evidence on Knightian and Bayesian Households Rdiger Bachmann,

Inflation Uncertainty - Survey Evidence on Knightian and Bayesian Households Rdiger Bachmann,

Inflation Uncertainty - Survey Evidence on Knightian and Bayesian Households Rdiger Bachmann, Kai Carstensen, Martin Schneider Deutsche Bundesbank Joint Conference on Household Expectations in Frankfurt, Germany September 28, 2019

286 views • 27 slides
Middle Market M&A: Proposed Changes to Reg S-X Rule 3-05 Presented to SEC Small Business

Middle Market M&A: Proposed Changes to Reg S-X Rule 3-05 Presented to SEC Small Business

Middle Market M&A: Proposed Changes to Reg S-X Rule 3-05 Presented to SEC Small Business Capital Formation Advisory Committee Matt Swartz Partner Pillsbury Winthrop Shaw Pittman, LLP Matt Swartz background Always thinks through

297 views • 12 slides
MAGNETIC TRAINING SOLUTIONS MAKING TRAINING STICK We make the boring things fun. And the fun

MAGNETIC TRAINING SOLUTIONS MAKING TRAINING STICK We make the boring things fun. And the fun

MAGNETIC TRAINING SOLUTIONS MAKING TRAINING STICK We make the boring things fun. And the fun things even more fun. Bei eing ng a be a bett tter er YO YOU! U! Do you have positive or negative biases when thinking about any of these

456 views • 35 slides
Dr Jennifer Whelan Driving Diversity: Developing more inclusive organisations Voice Project

Dr Jennifer Whelan Driving Diversity: Developing more inclusive organisations Voice Project

Dr Jennifer Whelan Driving Diversity: Developing more inclusive organisations Voice Project November 2016 Breakfast Series www.voiceproject.com E: enquiries@voiceproject.com why does diversity and inclusion drive performance? understanding

450 views • 16 slides
Advantage YPO Online Presentation October 15, 2014 How Can We Define Storytelling? Storytelling

Advantage YPO Online Presentation October 15, 2014 How Can We Define Storytelling? Storytelling

Storytelling for a Competitive Advantage YPO Online Presentation October 15, 2014 How Can We Define Storytelling? Storytelling (verb): Engaging the listeners imagination with words, images and actions to entertain, educate and influence;

249 views • 11 slides
PEERs Experience By: Abdul Ahlmahz Annie Leslie Students Creating Positive Change Toward a

PEERs Experience By: Abdul Ahlmahz Annie Leslie Students Creating Positive Change Toward a

PEERs Experience By: Abdul Ahlmahz Annie Leslie Students Creating Positive Change Toward a More Inclusive Engineering Overview About PEERs Current State of Engineering Underlying Causes Personal Stories & Why Diversity is

550 views • 23 slides

More recommend