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CHAPTER


                  Pitfalls and Opportunities

                  in the Development and                                     7

                  Evaluation of Artificial

                  Intelligence Systems



                                                      David G. Brown, Frank W. Samuelson
                                     US Food and Drug Administration, Silver Spring, MD, United States


                  CHAPTER OUTLINE
                  1. Introduction .......................................................................................................139
                  2. AI Development..................................................................................................142
                    2.1 Our Data Are Crap ............................................................................... 142
                    2.2 Our Algorithm Is Crap.......................................................................... 146
                  3. AI Evaluation .....................................................................................................148
                    3.1 Use of Data ........................................................................................ 148
                    3.2 Performance Measures ........................................................................ 149
                    3.3 Decision Thresholds ............................................................................ 154
                  4. Variability and Bias in Our Performance Estimates ...............................................154
                  5. Conclusion ........................................................................................................157
                  Acknowledgment.....................................................................................................158
                  References .............................................................................................................158


                  1. INTRODUCTION

                  Sergei, my appliance repairman, tells me my washing machine needs a new mother
                  board. I guess it does the crossword puzzle between loads. I look over at the car with
                  the funny hat in the next lane and there’s no driver. I read that it has no audio sensor
                  and can’t hear me honk at it. What else can’t it do? Does it understand that if a ball
                  rolls across the road a child may be in pursuit? This is the century of artificial intel-
                  ligence (AI), when computational intelligence (CI) algorithms show great promise
                  to tremendously improve the quality of our lives. Unfortunately, of course, it is
                  also the age of AI hype, in which systems without the intelligence of a cockroach
                  (Fig. 7.1) are touted as marvelous advances and cavalierly ceded the authority
                  over life-and-death decisions. We are warned that AI may be an existential threat
                  to our species; however, the dangers of AI at least for the foreseeable future pale
                  in comparison to those of AS (artificial stupidity), whereby CI algorithms are
                  used that are confusing, dysfunctional, and, yes, dangerous. In order not to become

                                                                                        139
                  Artificial Intelligence in the Age of Neural Networks and Brain Computing. https://doi.org/10.1016/B978-0-12-815480-9.00007-4
                  Copyright © 2019 Elsevier Inc. All rights reserved.
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