1 00:00:12,379 --> 00:00:08,900 good morning or whatever it is as most 2 00:00:16,760 --> 00:00:12,389 of you will recall perhaps somewhat 3 00:00:20,420 --> 00:00:16,770 painfully for the entire history of this 4 00:00:25,130 --> 00:00:20,430 noble organization we have rated before 5 00:00:28,640 --> 00:00:25,140 you and in your journal never-ending 6 00:00:32,600 --> 00:00:28,650 sequence of human machine anomalies 7 00:00:39,040 --> 00:00:32,610 experiments most of them I would like to 8 00:00:42,680 --> 00:00:39,050 think were squeaky clean well conceived 9 00:00:47,029 --> 00:00:42,690 with protocols protected against 10 00:00:51,080 --> 00:00:47,039 artifact large databases diligent 11 00:00:52,880 --> 00:00:51,090 operators seaworthy analytical business 12 00:00:57,139 --> 00:00:52,890 the whole nine yards good and clean 13 00:00:59,599 --> 00:00:57,149 experiments this is not the case of the 14 00:01:01,689 --> 00:00:59,609 topic I'm going to describe to you today 15 00:01:05,270 --> 00:01:01,699 quite the contrary 16 00:01:09,399 --> 00:01:05,280 this particular study I would have to 17 00:01:12,429 --> 00:01:09,409 regard as being quite sloppy nonetheless 18 00:01:16,280 --> 00:01:12,439 it revealed some rather interesting 19 00:01:19,340 --> 00:01:16,290 evidence that you may be interested in 20 00:01:24,370 --> 00:01:19,350 and you may even enjoy the sloppiness of 21 00:01:29,050 --> 00:01:24,380 the experiment in that array of 22 00:01:33,890 --> 00:01:29,060 experimental efforts that I alluded to 23 00:01:40,999 --> 00:01:33,900 one of the more active ones involves and 24 00:01:46,789 --> 00:01:41,009 a random robot you have most of you seen 25 00:01:49,100 --> 00:01:46,799 this guy in fact some of our co-authors 26 00:01:52,940 --> 00:01:49,110 and staff people are in his honor 27 00:01:55,249 --> 00:01:52,950 wearing t-shirts today with his image on 28 00:01:58,160 --> 00:01:55,259 them you will notice this Brenda has won 29 00:02:01,160 --> 00:01:58,170 on over it back at the room lisa has won 30 00:02:04,240 --> 00:02:01,170 on and I think there even a couple of 31 00:02:07,880 --> 00:02:04,250 others York is wearing his robot t-shirt 32 00:02:09,859 --> 00:02:07,890 this little guy is maybe yeah and I 33 00:02:13,520 --> 00:02:09,869 entered 10 inches in diameter he looks 34 00:02:16,580 --> 00:02:13,530 like a little samboni machine 35 00:02:20,030 --> 00:02:16,590 the froggy on a perched on the profit as 36 00:02:23,090 --> 00:02:20,040 the driver of this thing has a story all 37 00:02:25,040 --> 00:02:23,100 his own that I can't take time for but 38 00:02:31,150 --> 00:02:25,050 what happens here is there is an onboard 39 00:02:36,130 --> 00:02:31,160 re G and a processor yeah a code that 40 00:02:38,900 --> 00:02:36,140 communicates the output of that random 41 00:02:41,740 --> 00:02:38,910 processor into a set of instruction 42 00:02:44,450 --> 00:02:41,750 that's for the robot tells it move ahead 43 00:02:46,850 --> 00:02:44,460 turned it all right turn to the left and 44 00:02:50,000 --> 00:02:46,860 better yet tell us it how much to mow if 45 00:02:52,790 --> 00:02:50,010 I hadn't how much - how much to turn and 46 00:02:55,820 --> 00:02:52,800 so the thing executes a random 47 00:02:57,830 --> 00:02:55,830 2-dimensional walk on this table and the 48 00:03:00,380 --> 00:02:57,840 experiments have consisted of an 49 00:03:03,410 --> 00:03:00,390 operator and this is not the operator of 50 00:03:06,590 --> 00:03:03,420 these particular studies sitting 51 00:03:09,880 --> 00:03:06,600 adjacent to this platform in this table 52 00:03:12,770 --> 00:03:09,890 that's about four feet diameter and 53 00:03:15,400 --> 00:03:12,780 trying to induce the random motion of 54 00:03:18,830 --> 00:03:15,410 the thing to do with something anomalous 55 00:03:21,680 --> 00:03:18,840 eventually of course the the little 56 00:03:24,860 --> 00:03:21,690 froggie machine will tumble off the edge 57 00:03:28,880 --> 00:03:24,870 of the table and one set of protocols we 58 00:03:30,770 --> 00:03:28,890 believe we operated simply was can you 59 00:03:32,990 --> 00:03:30,780 get the machine to go off the other side 60 00:03:35,930 --> 00:03:33,000 or you can get it to come off on your 61 00:03:39,290 --> 00:03:35,940 side others we actually looked at the 62 00:03:42,170 --> 00:03:39,300 angles of exit or we'd say keep it on 63 00:03:45,290 --> 00:03:42,180 the table longer or get it off the table 64 00:03:49,070 --> 00:03:45,300 more promptly and and we've published on 65 00:03:50,830 --> 00:03:49,080 this theory references of available for 66 00:03:54,350 --> 00:03:50,840 those of you who want to follow that 67 00:03:57,259 --> 00:03:54,360 however the story now shifts into the 68 00:03:59,740 --> 00:03:57,269 present tense we were in the process 69 00:04:02,600 --> 00:03:59,750 somewhat of over a year and all of 70 00:04:05,600 --> 00:04:02,610 buttoning up the laboratory after 28 71 00:04:07,610 --> 00:04:05,610 years as we described last last year 72 00:04:10,479 --> 00:04:07,620 this meeting we actually decided to 73 00:04:13,370 --> 00:04:10,489 close down the university based 74 00:04:17,000 --> 00:04:13,380 experimental program and we were in the 75 00:04:21,949 --> 00:04:17,010 process packing up equipment unplugging 76 00:04:25,040 --> 00:04:21,959 stuff all sorts of moving personnel were 77 00:04:25,580 --> 00:04:25,050 coming in and out the idea of doing a 78 00:04:28,159 --> 00:04:25,590 control 79 00:04:31,490 --> 00:04:28,169 experiment was beyond question we had 80 00:04:34,310 --> 00:04:31,500 however working with us a student intern 81 00:04:38,360 --> 00:04:34,320 very interesting Chapman I don't want to 82 00:04:41,140 --> 00:04:38,370 violate his his anonymity but this was a 83 00:04:43,850 --> 00:04:41,150 fellow of regal worth from the African 84 00:04:46,909 --> 00:04:43,860 continent would spent time in France 85 00:04:51,310 --> 00:04:46,919 very articulate very medical student 86 00:04:54,050 --> 00:04:51,320 we'd been doing odd jobs with asana on a 87 00:04:57,290 --> 00:04:54,060 work-study program we came to me and 88 00:04:59,719 --> 00:04:57,300 said I love that robot experiment you 89 00:05:03,409 --> 00:04:59,729 did can I do I said that I was 90 00:05:05,810 --> 00:05:03,419 experiments I said this thing is is 91 00:05:08,409 --> 00:05:05,820 buttoned up it's in a box it doesn't 92 00:05:11,770 --> 00:05:08,419 work very well we've only used it for 93 00:05:15,050 --> 00:05:11,780 demonstration purposes no I want to try 94 00:05:18,469 --> 00:05:15,060 so a member of our senior staff when I 95 00:05:20,659 --> 00:05:18,479 think you can can guess and I said all 96 00:05:24,379 --> 00:05:20,669 right fine we haul it out we'll set it 97 00:05:26,560 --> 00:05:24,389 up again and we'll calibrate it and do 98 00:05:30,379 --> 00:05:26,570 the best we can to make it work and 99 00:05:32,390 --> 00:05:30,389 we'll run this person said I'll run one 100 00:05:35,260 --> 00:05:32,400 set of active trials and see what 101 00:05:37,790 --> 00:05:35,270 happens see if it's still viable and 102 00:05:39,560 --> 00:05:37,800 indeed it was as you will see in a 103 00:05:41,870 --> 00:05:39,570 moment and then handed and under the 104 00:05:47,990 --> 00:05:41,880 student who went on to do a much more 105 00:05:52,480 --> 00:05:48,000 extensive sequence of results now the 106 00:05:55,909 --> 00:05:52,490 results that this these two operators 107 00:05:58,640 --> 00:05:55,919 acquired is on this table you don't want 108 00:06:01,129 --> 00:05:58,650 to try to digest any of that I show it 109 00:06:04,279 --> 00:06:01,139 to you only so you're familiar with my 110 00:06:08,719 --> 00:06:04,289 nomenclature the two operators relabeled 111 00:06:11,180 --> 00:06:08,729 x and y the x was the senior in 112 00:06:16,190 --> 00:06:11,190 laboratory person may why was the 113 00:06:18,339 --> 00:06:16,200 student X did series a why did series B 114 00:06:19,460 --> 00:06:18,349 C and D and then there are these various 115 00:06:21,950 --> 00:06:19,470 concatenations 116 00:06:24,589 --> 00:06:21,960 and when the data we collected were the 117 00:06:27,170 --> 00:06:24,599 number of trials the number that went in 118 00:06:31,460 --> 00:06:27,180 the desired direction and then a bunch 119 00:06:33,740 --> 00:06:31,470 of observational parameters the total 120 00:06:37,399 --> 00:06:33,750 time it stayed on the table at secretary 121 00:06:38,780 --> 00:06:37,409 etc I should hastily interject that we 122 00:06:41,390 --> 00:06:38,790 decided just to get 123 00:06:44,660 --> 00:06:41,400 sitting on with as simply as possible 124 00:06:47,570 --> 00:06:44,670 you'd only do one protocol and that was 125 00:06:49,970 --> 00:06:47,580 the time of flight protocol get it off 126 00:06:52,640 --> 00:06:49,980 the table as quickly as possible those 127 00:06:54,770 --> 00:06:52,650 would be the short trials leave it on 128 00:06:57,290 --> 00:06:54,780 the table as long as you can though this 129 00:06:59,990 --> 00:06:57,300 would be the long files so we've got the 130 00:07:02,060 --> 00:07:00,000 average times the flight of an under 131 00:07:05,240 --> 00:07:02,070 these various conditions the 132 00:07:08,270 --> 00:07:05,250 distributions of those times some of the 133 00:07:10,850 --> 00:07:08,280 necessary statistical parameters the 134 00:07:13,430 --> 00:07:10,860 standard deviations and so on which 135 00:07:16,670 --> 00:07:13,440 permit us to calculate the t-squares 136 00:07:19,130 --> 00:07:16,680 the z-score is the probabilities against 137 00:07:24,620 --> 00:07:19,140 chance the Flex sizes are all that good 138 00:07:27,710 --> 00:07:24,630 stuff now I should again add that that 139 00:07:29,540 --> 00:07:27,720 all of this was done with people moving 140 00:07:32,390 --> 00:07:29,550 equipment through the laboratory 141 00:07:37,090 --> 00:07:32,400 jostling the table at one point the 142 00:07:42,040 --> 00:07:37,100 overhead camera that gaybies recorded 143 00:07:47,870 --> 00:07:46,040 got jostle wouldn't work anymore so I've 144 00:07:50,660 --> 00:07:47,880 said that a student look we've got to 145 00:07:53,270 --> 00:07:50,670 finish this get yourself a stopwatch and 146 00:07:56,870 --> 00:07:53,280 the poor kids that their timing the 147 00:08:00,020 --> 00:07:56,880 trials with a stopwatch and here are our 148 00:08:02,270 --> 00:08:00,030 data now and that's all the bad news but 149 00:08:06,230 --> 00:08:02,280 the good news is he got some striking 150 00:08:09,380 --> 00:08:06,240 effects as we will display a little or 151 00:08:13,100 --> 00:08:09,390 fasoli on this illustrative graph now 152 00:08:16,880 --> 00:08:13,110 here are operators again x and y here 153 00:08:20,260 --> 00:08:16,890 are this series they did a b c d and 154 00:08:23,870 --> 00:08:20,270 some of the combinations there up the 155 00:08:28,070 --> 00:08:23,880 the blue things the violet things here 156 00:08:30,950 --> 00:08:28,080 are the are the z-scores as computed by 157 00:08:35,030 --> 00:08:30,960 the usual statistical methods and he's 158 00:08:37,190 --> 00:08:35,040 magenta bars are the effect size i mean 159 00:08:39,920 --> 00:08:37,200 we can talk if you like how we compute 160 00:08:44,420 --> 00:08:39,930 an effect size in this experiment and 161 00:08:46,760 --> 00:08:44,430 look what happened our operator x did 162 00:08:48,800 --> 00:08:46,770 extraordinarily well but a green line 163 00:08:51,450 --> 00:08:48,810 that goes horizontally across here is 164 00:08:54,400 --> 00:08:51,460 the conventional 0.05 165 00:08:57,100 --> 00:08:54,410 statistical significance arbitrary 166 00:08:59,860 --> 00:08:57,110 criteria all right well he's punched way 167 00:09:02,260 --> 00:08:59,870 for really that the effect sizes way up 168 00:09:05,470 --> 00:09:02,270 here are beyond things we normally see 169 00:09:07,660 --> 00:09:05,480 and bear in mind please throughout these 170 00:09:10,600 --> 00:09:07,670 are all differential measurements we are 171 00:09:13,990 --> 00:09:10,610 distinguishing on this klutzy system 172 00:09:16,840 --> 00:09:14,000 between the long trial efforts the short 173 00:09:19,780 --> 00:09:16,850 trial efforts and not collectively so 174 00:09:22,960 --> 00:09:19,790 much as individually these data are the 175 00:09:26,470 --> 00:09:22,970 differences in adjacent trials tries to 176 00:09:29,260 --> 00:09:26,480 go high it's a time tries to go low it's 177 00:09:31,630 --> 00:09:29,270 a time subtract the number that's the 178 00:09:34,630 --> 00:09:31,640 measurable okay and obviously we 179 00:09:38,380 --> 00:09:34,640 alternate the sequence of these now 180 00:09:41,320 --> 00:09:38,390 comes to student series B that's very 181 00:09:44,920 --> 00:09:41,330 well also passed the significance 182 00:09:47,769 --> 00:09:44,930 criteria again big effect sizes then he 183 00:09:50,800 --> 00:09:47,779 does a second series and the poor guy 184 00:09:54,070 --> 00:09:50,810 goes backwards classical slime is 185 00:09:56,230 --> 00:09:54,080 phenomena way down here and he's trying 186 00:09:58,390 --> 00:09:56,240 to go high he's going lower he's trying