97 things about ethics everyone in data science should know : (Record no. 80350)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01888nam a22001937a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220825b2020 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789385889073 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.312 FRA-B |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Franks, Bill |
| 245 ## - TITLE STATEMENT | |
| Title | 97 things about ethics everyone in data science should know : |
| Remainder of title | collective wisdom from the experts / |
| Statement of responsibility, etc. | Bill Franks |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | India |
| Name of publisher, distributor, etc. | Shroff Publishers |
| Date of publication, distribution, etc. | 2020 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 323 p. |
| 365 ## - TRADE PRICE | |
| Price type code | INR |
| Price amount | 1250.00. |
| 500 ## - GENERAL NOTE | |
| General note | Most of the high-profile cases of real or perceived unethical activity in data science aren’t matters of bad intent. Rather, they occur because the ethics simply aren’t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult.<br/><br/>In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include:<br/><br/>Ethics Is Not a Binary Concept—Tim Wilson<br/>How to Approach Ethical Transparency—Rado Kotorov<br/>Unbiased ≠ Fair—Doug Hague<br/>Rules and Rationality—Christof Wolf Brenner<br/>The Truth About AI Bias—Cassie Kozyrkov<br/>Cautionary Ethics Tales—Sherrill Hayes<br/>Fairness in the Age of Algorithms—Anna Jacobson<br/>The Ethical Data Storyteller—Brent Dykes<br/>Introducing Ethicize, the Fully AI-Driven Cloud-Based Ethics Solution!—Brian O’Neill<br/>Be Careful with "Decisions of the Heart"—Hugh Watson<br/>Understanding Passive Versus Proactive Ethics—Bill Schmarzo. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data mining--Social aspects |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Big data |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence--Moral and ethical aspects |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Information technology--Moral and ethical aspects |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | 003-007 | BITS Pilani Hyderabad | BITS Pilani Hyderabad | General Stack (For lending) | 25/08/2022 | 006.312 FRA-B | 46266 | 26/07/2023 | 25/08/2022 | Books |
