Capsule 31_Artificial intelligence, the mirror of our society Version française: https://mediaserver.unige.ch/play/207030
jeudi 02 fév 2023
Capsules DSFA
1ELabNext
2Capsule 1_Hypothesis testing
3Capsule 2_Statistical models
4Capsule 3_Probability theory
5Capsule 4_Making data interoperable
6Capsule 5_Conditional probabilities
7Capsule 6_Discrete distributions
8Capsule 7_Expectation in statistics
9Capsule 8_Continuous random variables
10Capsule 9_Normal distribution
11Capsule 10_The societal risks of data collection
12Capsule 11_Setting up a data management plan
13Capsule 12_Anonymising or de-identifying data: nuances and issues
14Capsule 13_The empirical probability distribution
15Capsule 14_Statistical inference (1/3)
16Capsule 15_Statistical inference (2/3)
17Capsule 16_Statistical inference (3/3)
18Capsule 17_A la découverte des auto-encodeurs variationnels
19Capsule 18_Association measures
20Capsule 19_Treatment effects
21Capsule 20_Standardizing a database
22Capsule 21_Stylometric analysis
23Capsule 22_Geospatial data for health care
24Capsule 23_Environmental changes and satellite data
25Capsule 24_The challenges specific to data management
26Capsule 25_The questionnaire as a data collection tool
27Capsule 26_Le consentement en recherche: enjeux et modèles existants
28Capsule 27_Building the best model
29Capsule 28_The fascinating world of machine learning
30Capsule 29_Supervised learning via data annotation
31Capsule 30_Predicting clinical trial risks with machine learning
32Capsule 31_Artificial intelligence, the mirror of our society
33Capsule 32_The FAIR principles, issues and best practices
34Capsule 33_Connaître Les Systèmes Multi-agents
35Capsule 34_The benefits of working with an analyst
36Capsule 35_Administrative registers, a goldmine for researchers
37Capsule 36_Natural language processing and its application
38Capsule 37_Preparing your data for archiving
39Capsule 38_La méthode Design Science Research
40Capsule 39_Preserving the integrity of your data
41Capitule 40_Metadata, an underestimated facilitator
42Capsule 41_The 6 major challenges of data archiving 
43Capsule 42_IA et philanthropie: enjeux éthiques
44Capsule 43_La sélection de caractéristiques pour calibrer son modèle
45Capsule 44_Processing analog data
46Capsule 45_Big earth data and spatio-temporal analysis
47Capsule 46_Look at my numbers: the challenges of data visualization
48Capsule 47_Tips and tricks for making your datasets visible
49Capsule 48_FoNDUE, UNIGE's HTR infrastructure
50Capsule 49_Synthetic Aperture Radar, a new source of data
51Capsule 50_Les critères de validation d'un modèle
52Capsules 51_ Dynamic documents: an alternative to word processors
53Capsule 52_ Gestion de données: enjeux juridiques, lois et réglementations
54Capsule 53_Detecting changes to the earth's surface
55Capsule 54_Relever les défis environnementaux grâce à l'IA
56Capsule OAIS_ The OAIS standard, the conceptual basis for archiving
57Conducting an ethnographic interview
1ELabNext09:39
2Capsule 1_Hypothesis testing11:32
3Capsule 2_Statistical models10:15
4Capsule 3_Probability theory10:40
5Capsule 4_Making data interoperable10:45
6Capsule 5_Conditional probabilities08:24
7Capsule 6_Discrete distributions11:24
8Capsule 7_Expectation in statistics08:18
9Capsule 8_Continuous random variables09:27
10Capsule 9_Normal distribution10:50
11Capsule 10_The societal risks of data collection11:13
12Capsule 11_Setting up a data management plan09:00
13Capsule 12_Anonymising or de-identifying data: nuances and issues09:05
14Capsule 13_The empirical probability distribution10:13
15Capsule 14_Statistical inference (1/3)10:53
16Capsule 15_Statistical inference (2/3)10:57
17Capsule 16_Statistical inference (3/3)08:16
18Capsule 17_A la découverte des auto-encodeurs variationnels12:30
19Capsule 18_Association measures06:50
20Capsule 19_Treatment effects05:21
21Capsule 20_Standardizing a database09:30
22Capsule 21_Stylometric analysis08:25
23Capsule 22_Geospatial data for health care09:54
24Capsule 23_Environmental changes and satellite data10:58
25Capsule 24_The challenges specific to data management07:46
26Capsule 25_The questionnaire as a data collection tool07:52
27Capsule 26_Le consentement en recherche: enjeux et modèles existants09:23
28Capsule 27_Building the best model09:24
29Capsule 28_The fascinating world of machine learning09:48
30Capsule 29_Supervised learning via data annotation09:15
31Capsule 30_Predicting clinical trial risks with machine learning09:43
32Capsule 31_Artificial intelligence, the mirror of our society10:08
33Capsule 32_The FAIR principles, issues and best practices09:02
34Capsule 33_Connaître Les Systèmes Multi-agents10:00
35Capsule 34_The benefits of working with an analyst09:05
36Capsule 35_Administrative registers, a goldmine for researchers08:33
37Capsule 36_Natural language processing and its application10:07
38Capsule 37_Preparing your data for archiving10:18
39Capsule 38_La méthode Design Science Research10:43
40Capsule 39_Preserving the integrity of your data06:11
41Capitule 40_Metadata, an underestimated facilitator08:26
42Capsule 41_The 6 major challenges of data archiving 06:46
43Capsule 42_IA et philanthropie: enjeux éthiques08:53
44Capsule 43_La sélection de caractéristiques pour calibrer son modèle10:25
45Capsule 44_Processing analog data10:18
46Capsule 45_Big earth data and spatio-temporal analysis09:20
47Capsule 46_Look at my numbers: the challenges of data visualization07:26
48Capsule 47_Tips and tricks for making your datasets visible09:52
49Capsule 48_FoNDUE, UNIGE's HTR infrastructure14:42
50Capsule 49_Synthetic Aperture Radar, a new source of data07:37
51Capsule 50_Les critères de validation d'un modèle18:13
52Capsules 51_ Dynamic documents: an alternative to word processors08:29
53Capsule 52_ Gestion de données: enjeux juridiques, lois et réglementations08:31
54Capsule 53_Detecting changes to the earth's surface11:08
55Capsule 54_Relever les défis environnementaux grâce à l'IA08:28
56Capsule OAIS_ The OAIS standard, the conceptual basis for archiving02:31
57Conducting an ethnographic interview10:22
"With the digitization of society, artificial intelligence is becoming increasingly present in our daily lives. It makes recommendations that impact our lives. These algorithms are fed by billions of pieces of data (voices, texts, images, videos...) and become the mirror of an unequal society: women, but also racialized people are under-represented or represented in traditional roles. What can we do to ensure that the digital transition opens the way to a more inclusive world"