30+ Books to Help you Become an Ethical Data Scientist
In the digital age, the collection and analysis of vast amounts of data have become integral to business operations and decision-making processes. However, the unchecked use of data can lead to discrimination, bias, and other harmful consequences. Ethical data practices are essential to prevent these issues and promote fairness, transparency, and accountability in data-driven decisions.
Data Ethics: Principles and Challenges
The ethical compass in data science points toward principles such as:
Apart from these, we also need to assess how our data and AI activities relate to those values. To avoid conflict between our actions and our shared values, it is paramount to consider the ethical challenges below:
- Data Ownership
- Informed consent
- Intellectual property
- Data privacy
- Right to be forgotten
- Data bias
- Data quality
- Algorithm fairness
- Data misinterpretation
- Free choice
Books to Help you Become an Ethical Data Scientist
Meredith Broussard
4.21 avg rating — 268 ratings
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Cathy O'Neil
3.88 avg rating — 27,078 ratings
Invisible Women: Data Bias in a World Designed for Men
Caroline Criado Pérez
4.35 avg rating — 118,155 ratings
Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence
Kate Crawford
4.00 avg rating — 1,624 ratings
Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
Virginia Eubanks
4.01 avg rating — 2,542 ratings
The Signal and the Noise: Why So Many Predictions Fail—But Some Don't
Nate Silver
3.97 avg rating — 50,062 ratings
Hello World: Being Human in the Age of Algorithms
Hannah Fry
4.12 avg rating — 10,463 ratings
Data Feminism
Catherine D’Ignazio
4.35 avg rating — 1,146 ratings
MINDFUL AI - Reflections on Artificial Intelligence
Murat Durmus
4.00 avg rating — 7 ratings
The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power
Shoshana Zuboff
4.06 avg rating — 11,250 ratings
Thinking, Fast and Slow
Daniel Kahneman
4.18 avg rating — 499,439 ratings
Race After Technology: Abolitionist Tools for the New Jim Code
Ruha Benjamin
4.27 avg rating — 2,018 ratings
Algorithms of Oppression: How Search Engines Reinforce Racism
Safiya Umoja Noble
3.90 avg rating — 3,486 ratings
Working with Coders: A Guide to Software Development for the Perplexed Non-Techie
Patrick Gleeson
4.00 avg rating — 58 ratings
Platform Capitalism
Nick Srnicek
3.93 avg rating — 1,164 ratings
The Alignment Problem: Machine Learning and Human Values
Brian Christian
4.40 avg rating — 2,963 ratings
Dark Matters: On the Surveillance of Blackness
Simone Browne
4.46 avg rating — 498 ratings
Design Justice: Community-Led Practices to Build the Worlds We Need
Sasha Costanza-Chock
4.20 avg rating — 442 ratings
Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass
Mary L. Gray
3.72 avg rating — 390 ratings
Artificial Unintelligence: How Computers Misunderstand the World
Meredith Broussard
3.79 avg rating — 782 ratings
Quiet: The Power of Introverts in a World That Can't Stop Talking
Susan Cain
4.08 avg rating — 435,949 ratings
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Seth Stephens-Davidowitz
3.91 avg rating — 40,334 ratings
97 Things Every Programmer Should Know: Collective Wisdom from the Experts
Kevlin Henney
3.63 avg rating — 1,940 ratings
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Aurélien Géron
4.56 avg rating — 2,460 ratings
Cognitive Biases: A Brief Overview of Over 160 Cognitive Biases + Bonus Chapter: Algorithmic Bias
Murat Durmus
4.40 avg rating — 5 ratings
A Human's Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control
Kartik Hosanagar
3.88 avg rating — 402 ratings
Think Like a Data Scientist: Tackle the data science process step-by-step
Brian Godsey
3.81 avg rating — 88 ratings
The Hundred-Page Machine Learning Book
Andriy Burkov
4.26 avg rating — 1,187 ratings
Algorithms to Live By: What Computers Can Teach Us About Solving Human Problems
Brian Christian
4.13 avg rating — 31,231 ratings
The Future of Feeling: Building Empathy in a Tech-Obsessed World
Kaitlin Ugolik Phillips
3.21 avg rating — 2,143 ratings
Beyond Hashtag Activism: Comprehensive Justice in a Complicated Age
Mae Elise Cannon
4.28 avg rating — 60 ratings
Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech
Sara Wachter-Boettcher
4.08 avg rating — 2,445 ratings
The Ethical Algorithm: The Science of Socially Aware Algorithm Design
Michael Kearns
4.12 avg rating — 578 ratings
Queer Data: Using Gender, Sex and Sexuality Data for Action
Kevin Guyan
4.01 avg rating — 72 ratings
Bad Blood: Secrets and Lies in a Silicon Valley Startup
John Carreyrou
4.41 avg rating — 260,250 ratings
How We Became Posthuman: Virtual Bodies in Cybernetics, Literature, and Informatics
N. Katherine Hayles
4.06 avg rating — 843 ratings
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