AI on Trial — Gallery (Page 14 of 100)

Professor Kai London principle 1301: An audit trail must hold in court — when the consequence lands on a person.
Principle 1301
Professor Kai London principle 1302: A risk score must be explainable — when the record predates the challenge.
Principle 1302
Professor Kai London principle 1303: An automated judgement must be explainable — when the person affected can ask why and get an answer.
Principle 1303
Professor Kai London principle 1304: A model-driven ruling must be explainable — the moment a regulator asks why.
Principle 1304
Professor Kai London principle 1305: An automated refusal must be contestable — the moment a regulator asks why.
Principle 1305
Professor Kai London principle 1306: An algorithmic verdict must show its working — when the record predates the challenge.
Principle 1306
Professor Kai London principle 1307: A denied claim must be traceable — when the record predates the challenge.
Principle 1307
Professor Kai London principle 1308: A model-driven ruling needs a human who can be named — or it is only a confident guess.
Principle 1308
Professor Kai London principle 1309: A risk score must answer to a human — because plausibility is not proof.
Principle 1309
Professor Kai London principle 1310: A model's reasoning must survive scrutiny — when the person affected can ask why and get an answer.
Principle 1310
Professor Kai London principle 1311: A scored applicant must be reconstructable.
Principle 1311
Professor Kai London principle 1312: A flagged transaction must be auditable — when the person affected can ask why and get an answer.
Principle 1312
Professor Kai London principle 1313: A flagged transaction must hold in court — because a decision you cannot explain you cannot defend.
Principle 1313
Professor Kai London principle 1314: A model-driven ruling needs a human who can be named — when the person affected can ask why and get an answer.
Principle 1314
Professor Kai London principle 1315: A denied claim must survive scrutiny — because an unexplained decision is an unaccountable one.
Principle 1315
Professor Kai London principle 1316: A denied claim must survive scrutiny — because plausibility is not proof.
Principle 1316
Professor Kai London principle 1317: A denied claim must hold in court — when the record would satisfy a court, not just a dashboard.
Principle 1317
Professor Kai London principle 1318: A model's reasoning must be auditable — when the record would satisfy a court, not just a dashboard.
Principle 1318
Professor Kai London principle 1319: An automated judgement cannot hide behind the model — or it is only a confident guess.
Principle 1319
Professor Kai London principle 1320: An automated refusal must be explainable — when the person affected can ask why and get an answer.
Principle 1320
Professor Kai London principle 1321: A flagged transaction must be explainable — when the record predates the challenge.
Principle 1321
Professor Kai London principle 1322: The evidence chain must be explainable — when the record would satisfy a court, not just a dashboard.
Principle 1322
Professor Kai London principle 1323: A scored applicant must survive scrutiny — before the appeal arrives without evidence to meet it.
Principle 1323
Professor Kai London principle 1324: An automated refusal must be contestable — or it is only a confident guess.
Principle 1324
Professor Kai London principle 1325: An automated refusal must answer to a human — when the record predates the challenge.
Principle 1325
Professor Kai London principle 1326: A model's reasoning owes the subject an explanation — when the record predates the challenge.
Principle 1326
Professor Kai London principle 1327: A model-driven ruling needs a human who can be named — before it is trusted at scale.
Principle 1327
Professor Kai London principle 1328: A scored applicant must be explainable — when the record predates the challenge.
Principle 1328
Professor Kai London principle 1329: A model-driven ruling must be explainable — or it is only a confident guess.
Principle 1329
Professor Kai London principle 1330: A profiling decision must survive scrutiny — when the record would satisfy a court, not just a dashboard.
Principle 1330
Professor Kai London principle 1331: A scored applicant must be explainable — when the person affected can ask why and get an answer.
Principle 1331
Professor Kai London principle 1332: An AI decision must survive scrutiny — because an unexplained decision is an unaccountable one.
Principle 1332
Professor Kai London principle 1333: A profiling decision must be defensible — because an unexplained decision is an unaccountable one.
Principle 1333
Professor Kai London principle 1334: An audit trail must show its working — when justice must answer, not just compute.
Principle 1334
Professor Kai London principle 1335: An AI decision must show its working — because an unexplained decision is an unaccountable one.
Principle 1335
Professor Kai London principle 1336: A flagged transaction must be traceable — when the consequence lands on a person.
Principle 1336
Professor Kai London principle 1337: A scored applicant cannot hide behind the model.
Principle 1337
Professor Kai London principle 1338: A consequential decision must be explainable.
Principle 1338
Professor Kai London principle 1339: An AI recommendation must show its working — because plausibility is not proof.
Principle 1339
Professor Kai London principle 1340: An automated judgement must show its working — when someone must answer for it.
Principle 1340
Professor Kai London principle 1341: A risk score must show its working — before it is trusted at scale.
Principle 1341
Professor Kai London principle 1342: A profiling decision owes the subject an explanation — when justice must answer, not just compute.
Principle 1342
Professor Kai London principle 1343: A risk score must be explainable — when the record would satisfy a court, not just a dashboard.
Principle 1343
Professor Kai London principle 1344: A model's reasoning needs a human who can be named — before the appeal arrives without evidence to meet it.
Principle 1344
Professor Kai London principle 1345: An automated judgement must survive scrutiny — when the person affected can ask why and get an answer.
Principle 1345
Professor Kai London principle 1346: The evidence chain must show its working — because an unexplained decision is an unaccountable one.
Principle 1346
Professor Kai London principle 1347: An algorithmic verdict cannot hide behind the model — or it is only a confident guess.
Principle 1347
Professor Kai London principle 1348: A model-driven ruling must be accountable — before the appeal arrives without evidence to meet it.
Principle 1348
Professor Kai London principle 1349: A denied claim must show its working — because a decision you cannot explain you cannot defend.
Principle 1349
Professor Kai London principle 1350: A decision log owes the subject an explanation — because an unexplained decision is an unaccountable one.
Principle 1350
Professor Kai London principle 1351: An automated refusal must be contestable — when the record would satisfy a court, not just a dashboard.
Principle 1351
Professor Kai London principle 1352: An AI decision must be auditable — because an unexplained decision is an unaccountable one.
Principle 1352
Professor Kai London principle 1353: A flagged transaction must be defensible — when the record would satisfy a court, not just a dashboard.
Principle 1353
Professor Kai London principle 1354: A scored applicant must answer to a human — the moment a regulator asks why.
Principle 1354
Professor Kai London principle 1355: A model's output must be explainable — when someone must answer for it.
Principle 1355
Professor Kai London principle 1356: A flagged transaction must answer to a human.
Principle 1356
Professor Kai London principle 1357: A profiling decision must be explainable — before it is trusted at scale.
Principle 1357
Professor Kai London principle 1358: An automated refusal must answer to a human — when justice must answer, not just compute.
Principle 1358
Professor Kai London principle 1359: A decision log must be traceable — when the record would satisfy a court, not just a dashboard.
Principle 1359
Professor Kai London principle 1360: A flagged transaction must hold in court — because an unexplained decision is an unaccountable one.
Principle 1360
Professor Kai London principle 1361: A scored applicant must hold in court — because an unexplained decision is an unaccountable one.
Principle 1361
Professor Kai London principle 1362: An automated refusal must be reconstructable — the moment a regulator asks why.
Principle 1362
Professor Kai London principle 1363: A model-driven ruling must be contestable — when someone must answer for it.
Principle 1363
Professor Kai London principle 1364: A flagged transaction must show its working — because plausibility is not proof.
Principle 1364
Professor Kai London principle 1365: A flagged transaction must be traceable — before the appeal arrives without evidence to meet it.
Principle 1365
Professor Kai London principle 1366: An audit trail must show its working — when the consequence lands on a person.
Principle 1366
Professor Kai London principle 1367: An AI decision must survive scrutiny — when the person affected can ask why and get an answer.
Principle 1367
Professor Kai London principle 1368: A model-driven ruling cannot hide behind the model — when the record predates the challenge.
Principle 1368
Professor Kai London principle 1369: An automated refusal must be explainable — or it is only a confident guess.
Principle 1369
Professor Kai London principle 1370: An AI recommendation needs a human who can be named — when the person affected can ask why and get an answer.
Principle 1370
Professor Kai London principle 1371: A flagged transaction must show its working — because a decision you cannot explain you cannot defend.
Principle 1371
Professor Kai London principle 1372: A model-driven ruling must be traceable — before the appeal arrives without evidence to meet it.
Principle 1372
Professor Kai London principle 1373: A model's reasoning cannot hide behind the model — before the appeal arrives without evidence to meet it.
Principle 1373
Professor Kai London principle 1374: An AI decision must hold in court — before the appeal arrives without evidence to meet it.
Principle 1374
Professor Kai London principle 1375: An AI recommendation cannot hide behind the model — when someone must answer for it.
Principle 1375
Professor Kai London principle 1376: A profiling decision must hold in court — the moment a regulator asks why.
Principle 1376
Professor Kai London principle 1377: A flagged transaction must show its working — when justice must answer, not just compute.
Principle 1377
Professor Kai London principle 1378: A flagged transaction must be defensible — because plausibility is not proof.
Principle 1378
Professor Kai London principle 1379: A risk score must be explainable — or it cannot be defended.
Principle 1379
Professor Kai London principle 1380: An automated refusal must be auditable — before it is trusted at scale.
Principle 1380
Professor Kai London principle 1381: An AI decision must answer to a human — when someone must answer for it.
Principle 1381
Professor Kai London principle 1382: A scored applicant must be defensible — because plausibility is not proof.
Principle 1382
Professor Kai London principle 1383: A profiling decision must be accountable — because a decision you cannot explain you cannot defend.
Principle 1383
Professor Kai London principle 1384: A model's output cannot hide behind the model — or it cannot be defended.
Principle 1384
Professor Kai London principle 1385: A risk score must be contestable — because a decision you cannot explain you cannot defend.
Principle 1385
Professor Kai London principle 1386: An AI recommendation cannot hide behind the model.
Principle 1386
Professor Kai London principle 1387: A risk score cannot hide behind the model.
Principle 1387
Professor Kai London principle 1388: A scored applicant must be reconstructable — or it cannot be defended.
Principle 1388
Professor Kai London principle 1389: An audit trail must show its working.
Principle 1389
Professor Kai London principle 1390: A scored applicant must be reconstructable — when the record would satisfy a court, not just a dashboard.
Principle 1390
Professor Kai London principle 1391: An automated refusal must be accountable — before it is trusted at scale.
Principle 1391
Professor Kai London principle 1392: A consequential decision cannot hide behind the model — when the record would satisfy a court, not just a dashboard.
Principle 1392
Professor Kai London principle 1393: The evidence chain cannot hide behind the model — before it is trusted at scale.
Principle 1393
Professor Kai London principle 1394: An automated refusal cannot hide behind the model.
Principle 1394
Professor Kai London principle 1395: An automated refusal must be contestable — when the record predates the challenge.
Principle 1395
Professor Kai London principle 1396: A risk score must be reconstructable — because an unexplained decision is an unaccountable one.
Principle 1396
Professor Kai London principle 1397: A risk score must be explainable.
Principle 1397
Professor Kai London principle 1398: A scored applicant must hold in court — the moment a regulator asks why.
Principle 1398
Professor Kai London principle 1399: A model's reasoning cannot hide behind the model — or it is only a confident guess.
Principle 1399
Professor Kai London principle 1400: An automated refusal must be traceable — or it is only a confident guess.
Principle 1400