Wanted: Human-AI Translators

INTRODUCTION:
A MANUAL FOR AI TRANSLATORS 8

1 ALGORITHMS 30
Smart, smarter, smartest 31
Algorithms 32
Neural networks 35
Learning in three flavours 37
Top model wanted 42
A self-driving crash 46
Moravec’s paradox 49
People versus machines 52
Algorithmic bias 57
A ‘black box’ 60
‘Move 78’ 61
INTERVIEW WITH SASCHA SCHUBERT 63
INTERVIEW WITH SERGEY YABLONSKY 66
INTERVIEW WITH SAMI MAHROUM 68

2 DATA 71
The oil of smart systems 72
The five dimensions 75
Health data 81
Clicks and personal insights 83
GDPR 87
Solid 88
INTERVIEW WITH RUBEN VERBORGH 90
INTERVIEW WITH FREDERIC PIVETTA 92
INTERVIEW WITH JACQUES LUDIK 95

3 HARDWARE 98
Who controls AI? 99
AI becomes tangible 101
Madonna versus Basic 102
Basic structure 106
AI accelerators 108
In the clouds 111
Solutions at the edge 113
Tech giants 116
Dot-com bubble 119
Are we catching up? 120
INTERVIEW WITH FILIP PINTELON 122
INTERVIEW WITH TIJS WILBRINK 125
INTERVIEW WITH ERIC MEJDRICH 127

4 AUTOMATED DECISIONING 129
Is AI stealing our jobs? 130
Classification systems 132
Image recognition 135
Speech recognition 137
Misleading AI 140
Context matters 142
Bankruptcy 144
AI in the boardroom 146
Who wins? 148
INTERVIEW WITH TOBIAS GROSSE-PUPPENDAHL 152
INTERVIEW WITH STEPHANIE COX 154
INTERVIEW WITH RUBEN MISSINNE 157

5 ETHICAL AI 160
How do we become responsible? 161
Unexpected consequences 164
The Hippocratic Oath 166
Four fundamental principles 168
Red queen hypothesis 174
Ethical guidelines for AI 175
Incorrect prohibition 177
Asimov’s laws 178
INTERVIEW WITH CÉCILE HUET 180
INTERVIEW WITH NATHALIE SMUHA 183
INTERVIEW WITH KATLEEN GABRIELS 186

6 CONCLUSIONS:
FROM BRAIN TO PLANT 189
The future of AI 190
Four phases 194
Brain chauvinism 196
Other forms of intelligence 199
The Celestine Prophecy 206

Author’s note 209
Endnotes 211