LEADER 01173nam--2200385---450- 001 990002056560203316 005 20090603103155.0 035 $a000205656 035 $aUSA01000205656 035 $a(ALEPH)000205656USA01 035 $a000205656 100 $a20041006d1984----km-y0itay0103----ba 101 $ager 102 $aDE 105 $a||||||||001yy 200 1 $a<> Kaufrecht$eKaufvertrag, Haftung bei Rechts- und Sachmangeln, besondere Arten des Kaufs$fvon Bruno Bergerfurth und Lutz Menard 205 $a3. neubearteitete Aufl 210 $aFreiburg am Breisgau$cHaufe$d1984 215 $a396 p.$d20 cm 410 0$12001 454 1$12001 461 1$1001-------$12001 606 0 $aVendita$yGermania occidentale$xLegislazione 676 $a346.02 700 1$aBERGERFURTH,$bBruno$0226620 701 1$aMENARD,$bLutz$0566921 801 0$aIT$bsalbc$gISBD 912 $a990002056560203316 951 $aXXV.1.M 218 (IG XXI 219)$b9261 E.C.$cIG XXI$d00231263 959 $aBK 969 $aGIU 979 $aSIAVPROV$b10$c20041006$lUSA01$h1315 979 $aRSIAV4$b90$c20090603$lUSA01$h1031 996 $aKaufrecht$91043318 997 $aUNISA LEADER 03359nam 2200637 - 450 001 9910803896803321 005 20251002100058.0 010 $a0192847260 010 $a9780192847263$bhardback 010 $a0192847279 010 $a9780192847270$bpaperback 035 $a(OCoLC)on1273469063 100 $a20210908d2022 uy 0 101 0 $aeng 181 $2rdacontent 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aData science ethics $econcepts, techniques and cautionary tales /$fDavid Martens 210 1$aOxford, United Kingdom :$cOxford University Press,$d[2022] 215 $axii, 255 pages $cillustrations (some color), color map ;$d24 cm 320 $aIncludes bibliographical references and index. 330 $aData science ethics is all about what is right and wrong when conducting data science. Data science has so far been primarily used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. While data scientists and business managers are not inherently unethical, they are not trained to weigh the ethical considerations that come from their work - Data Science Ethics addresses this increasingly significant gap and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques. Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data. --$cProvided by publisher. 531 $aOxford, United Kingdom : 606 $aBig data$xMoral and ethical aspects 606 $aData mining$xMoral and ethical aspects 606 $aDonne?es volumineuses$xAspect moral 606 $aExploration de donne?es (Informatique)$xAspect moral 606 $aMATHEMATICS / General$2bisacsh 615 0$aBig data$xMoral and ethical aspects. 615 0$aData mining$xMoral and ethical aspects. 615 6$aDonne?es volumineuses$xAspect moral. 615 6$aExploration de donne?es (Informatique)$xAspect moral. 615 7$aMATHEMATICS / General. 676 $a005.7 701 1$aMertens$01588595 801 0$bYDX 801 1$bYDX 801 2$bBDX 801 2$bUKMGB 801 2$bOCLCO 801 2$bTOH 801 2$bKKU 801 2$bFIE 801 2$bYDX 801 2$bDLC 901 $aBK 912 $a9910803896803321 925 0 $aacquire$b1 shelf copy$xpolicy default 952 $aSOC 188$b478/2024$fFSPBC 952 $a005.74-MAR-1$b291/2025$fSC1 955 $brk07 2023-04-26 z-processor$irk07 2023-05-04 to CMD 959 $aFSPBC 959 $aSC1 996 $aData science ethics$93882531 997 $aUNINA