AI on Trial — Gallery (Page 16 of 100)

Professor Kai London principle 1501: A model's reasoning needs a human who can be named — when the consequence lands on a person.
Principle 1501
Professor Kai London principle 1502: An automated refusal must survive scrutiny — or it cannot be defended.
Principle 1502
Professor Kai London principle 1503: A model's reasoning must be defensible — before the appeal arrives without evidence to meet it.
Principle 1503
Professor Kai London principle 1504: A consequential decision owes the subject an explanation — or it is only a confident guess.
Principle 1504
Professor Kai London principle 1505: An automated judgement must be defensible — because an unexplained decision is an unaccountable one.
Principle 1505
Professor Kai London principle 1506: A denied claim must be reconstructable — because a decision you cannot explain you cannot defend.
Principle 1506
Professor Kai London principle 1507: A profiling decision must show its working — when someone must answer for it.
Principle 1507
Professor Kai London principle 1508: A decision log owes the subject an explanation — the moment a regulator asks why.
Principle 1508
Professor Kai London principle 1509: A model-driven ruling must be auditable — when the person affected can ask why and get an answer.
Principle 1509
Professor Kai London principle 1510: An automated judgement must be reconstructable — when the record would satisfy a court, not just a dashboard.
Principle 1510
Professor Kai London principle 1511: An automated refusal needs a human who can be named — before it is trusted at scale.
Principle 1511
Professor Kai London principle 1512: The evidence chain needs a human who can be named — when the consequence lands on a person.
Principle 1512
Professor Kai London principle 1513: An audit trail must be defensible — or it is only a confident guess.
Principle 1513
Professor Kai London principle 1514: The evidence chain must be auditable — before the appeal arrives without evidence to meet it.
Principle 1514
Professor Kai London principle 1515: A profiling decision must show its working — or it is only a confident guess.
Principle 1515
Professor Kai London principle 1516: An AI recommendation owes the subject an explanation — or it is only a confident guess.
Principle 1516
Professor Kai London principle 1517: A profiling decision must be contestable — before it is trusted at scale.
Principle 1517
Professor Kai London principle 1518: An audit trail must show its working — when the record predates the challenge.
Principle 1518
Professor Kai London principle 1519: A risk score must show its working — because a decision you cannot explain you cannot defend.
Principle 1519
Professor Kai London principle 1520: A scored applicant owes the subject an explanation — because plausibility is not proof.
Principle 1520
Professor Kai London principle 1521: A scored applicant owes the subject an explanation — when the person affected can ask why and get an answer.
Principle 1521
Professor Kai London principle 1522: An algorithmic verdict needs a human who can be named — or it is only a confident guess.
Principle 1522
Professor Kai London principle 1523: A denied claim must be auditable — the moment a regulator asks why.
Principle 1523
Professor Kai London principle 1524: A denied claim must be defensible — when the record predates the challenge.
Principle 1524
Professor Kai London principle 1525: An AI recommendation must hold in court — because an unexplained decision is an unaccountable one.
Principle 1525
Professor Kai London principle 1526: A risk score must survive scrutiny.
Principle 1526
Professor Kai London principle 1527: A consequential decision must be defensible — when the person affected can ask why and get an answer.
Principle 1527
Professor Kai London principle 1528: A model's output must show its working — the moment a regulator asks why.
Principle 1528
Professor Kai London principle 1529: A flagged transaction cannot hide behind the model — when the person affected can ask why and get an answer.
Principle 1529
Professor Kai London principle 1530: An algorithmic verdict must show its working — before the appeal arrives without evidence to meet it.
Principle 1530
Professor Kai London principle 1531: An automated refusal must be auditable — because plausibility is not proof.
Principle 1531
Professor Kai London principle 1532: A model-driven ruling cannot hide behind the model — when justice must answer, not just compute.
Principle 1532
Professor Kai London principle 1533: An automated refusal must show its working — when the consequence lands on a person.
Principle 1533
Professor Kai London principle 1534: A model's output must hold in court — when the record would satisfy a court, not just a dashboard.
Principle 1534
Professor Kai London principle 1535: An algorithmic verdict needs a human who can be named — when the consequence lands on a person.
Principle 1535
Professor Kai London principle 1536: A denied claim must be auditable — when the record predates the challenge.
Principle 1536
Professor Kai London principle 1537: A model's reasoning needs a human who can be named.
Principle 1537
Professor Kai London principle 1538: An algorithmic verdict must show its working — before it is trusted at scale.
Principle 1538
Professor Kai London principle 1539: An AI recommendation owes the subject an explanation.
Principle 1539
Professor Kai London principle 1540: An automated judgement must be defensible — when the record would satisfy a court, not just a dashboard.
Principle 1540
Professor Kai London principle 1541: A scored applicant must answer to a human.
Principle 1541
Professor Kai London principle 1542: A profiling decision must be defensible.
Principle 1542
Professor Kai London principle 1543: An AI recommendation owes the subject an explanation — the moment a regulator asks why.
Principle 1543
Professor Kai London principle 1544: An AI recommendation needs a human who can be named — because plausibility is not proof.
Principle 1544
Professor Kai London principle 1545: A model's reasoning must be contestable — because an unexplained decision is an unaccountable one.
Principle 1545
Professor Kai London principle 1546: An AI decision needs a human who can be named — when the consequence lands on a person.
Principle 1546
Professor Kai London principle 1547: A flagged transaction must be auditable — or it cannot be defended.
Principle 1547
Professor Kai London principle 1548: An AI decision must show its working.
Principle 1548
Professor Kai London principle 1549: A scored applicant must survive scrutiny — because plausibility is not proof.
Principle 1549
Professor Kai London principle 1550: A denied claim must be reconstructable — or it is only a confident guess.
Principle 1550
Professor Kai London principle 1551: A flagged transaction must hold in court — when the consequence lands on a person.
Principle 1551
Professor Kai London principle 1552: An AI recommendation must be explainable — when the record would satisfy a court, not just a dashboard.
Principle 1552
Professor Kai London principle 1553: The evidence chain cannot hide behind the model — when the record predates the challenge.
Principle 1553
Professor Kai London principle 1554: A flagged transaction needs a human who can be named — before the appeal arrives without evidence to meet it.
Principle 1554
Professor Kai London principle 1555: An audit trail must show its working — the moment a regulator asks why.
Principle 1555
Professor Kai London principle 1556: A model's reasoning needs a human who can be named — or it cannot be defended.
Principle 1556
Professor Kai London principle 1557: The evidence chain must hold in court.
Principle 1557
Professor Kai London principle 1558: A decision log needs a human who can be named.
Principle 1558
Professor Kai London principle 1559: An automated refusal must answer to a human — because a decision you cannot explain you cannot defend.
Principle 1559
Professor Kai London principle 1560: An audit trail must answer to a human — the moment a regulator asks why.
Principle 1560
Professor Kai London principle 1561: A scored applicant needs a human who can be named — before it is trusted at scale.
Principle 1561
Professor Kai London principle 1562: An audit trail must be explainable — before the appeal arrives without evidence to meet it.
Principle 1562
Professor Kai London principle 1563: An automated judgement cannot hide behind the model — before it is trusted at scale.
Principle 1563
Professor Kai London principle 1564: An AI decision must be explainable — before the appeal arrives without evidence to meet it.
Principle 1564
Professor Kai London principle 1565: A decision log owes the subject an explanation — when the consequence lands on a person.
Principle 1565
Professor Kai London principle 1566: An audit trail must show its working — or it cannot be defended.
Principle 1566
Professor Kai London principle 1567: An automated refusal cannot hide behind the model — because plausibility is not proof.
Principle 1567
Professor Kai London principle 1568: A risk score must be accountable — when the record predates the challenge.
Principle 1568
Professor Kai London principle 1569: An automated judgement must show its working — when the record would satisfy a court, not just a dashboard.
Principle 1569
Professor Kai London principle 1570: The evidence chain must be defensible — before the appeal arrives without evidence to meet it.
Principle 1570
Professor Kai London principle 1571: A consequential decision must be contestable — when the record would satisfy a court, not just a dashboard.
Principle 1571
Professor Kai London principle 1572: A consequential decision cannot hide behind the model — because a decision you cannot explain you cannot defend.
Principle 1572
Professor Kai London principle 1573: A denied claim must be traceable — because plausibility is not proof.
Principle 1573
Professor Kai London principle 1574: A consequential decision cannot hide behind the model.
Principle 1574
Professor Kai London principle 1575: A decision log must be explainable — when the person affected can ask why and get an answer.
Principle 1575
Professor Kai London principle 1576: A denied claim must answer to a human — before it is trusted at scale.
Principle 1576
Professor Kai London principle 1577: A model-driven ruling must be accountable — the moment a regulator asks why.
Principle 1577
Professor Kai London principle 1578: A scored applicant cannot hide behind the model — when the consequence lands on a person.
Principle 1578
Professor Kai London principle 1579: An AI decision must be reconstructable — because an unexplained decision is an unaccountable one.
Principle 1579
Professor Kai London principle 1580: A risk score must be contestable — because plausibility is not proof.
Principle 1580
Professor Kai London principle 1581: An AI decision owes the subject an explanation — when someone must answer for it.
Principle 1581
Professor Kai London principle 1582: A profiling decision needs a human who can be named — before the appeal arrives without evidence to meet it.
Principle 1582
Professor Kai London principle 1583: A model-driven ruling must be contestable — because a decision you cannot explain you cannot defend.
Principle 1583
Professor Kai London principle 1584: A profiling decision owes the subject an explanation — before it is trusted at scale.
Principle 1584
Professor Kai London principle 1585: A model-driven ruling must survive scrutiny.
Principle 1585
Professor Kai London principle 1586: A scored applicant must answer to a human — or it is only a confident guess.
Principle 1586
Professor Kai London principle 1587: An audit trail owes the subject an explanation — because an unexplained decision is an unaccountable one.
Principle 1587
Professor Kai London principle 1588: An automated refusal must show its working — because plausibility is not proof.
Principle 1588
Professor Kai London principle 1589: A risk score must be accountable — when the consequence lands on a person.
Principle 1589
Professor Kai London principle 1590: A risk score must be accountable — before the appeal arrives without evidence to meet it.
Principle 1590
Professor Kai London principle 1591: An automated refusal must be defensible — when justice must answer, not just compute.
Principle 1591
Professor Kai London principle 1592: A model's reasoning must hold in court — because an unexplained decision is an unaccountable one.
Principle 1592
Professor Kai London principle 1593: A consequential decision needs a human who can be named — the moment a regulator asks why.
Principle 1593
Professor Kai London principle 1594: A scored applicant must survive scrutiny — the moment a regulator asks why.
Principle 1594
Professor Kai London principle 1595: An automated judgement must be reconstructable — when the person affected can ask why and get an answer.
Principle 1595
Professor Kai London principle 1596: An audit trail must be defensible — before the appeal arrives without evidence to meet it.
Principle 1596
Professor Kai London principle 1597: A profiling decision must be accountable — when the record predates the challenge.
Principle 1597
Professor Kai London principle 1598: The evidence chain must be contestable — because an unexplained decision is an unaccountable one.
Principle 1598
Professor Kai London principle 1599: A consequential decision needs a human who can be named — when the record predates the challenge.
Principle 1599
Professor Kai London principle 1600: A denied claim must answer to a human — when someone must answer for it.
Principle 1600