Lesson 10: A closer look at Diligence | AI Fluency: Framework & Foundations Course — Transcript

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1. 0:11In this video, we'll examine the
2. 0:13diligence competency from the AI fluency
3. 0:15framework. Remember that AI fluency
4. 0:18means working with AI effectively,
5. 0:20efficiently, ethically, and safely.
6. 0:24While the other three competencies
7. 0:26primarily address effectiveness and
8. 0:28efficiency, diligence focuses mostly on
9. 0:31the ethical and safety aspects that are
10. 0:33just as crucial for successful AI
11. 0:37collaboration. At its heart, diligence
12. 0:40is about taking responsibility for your
13. 0:42AI interactions. It's the dimension of
14. 0:45AI fluency that ensures your use of AI
15. 0:49systems is not only productive but also
16. 0:52rigorous, transparent, and accountable.
17. 0:55Unlike the other competencies that
18. 0:57primarily focus on getting results,
19. 1:00diligence asks us to consider broader
20. 1:02questions that are nevertheless critical
21. 1:04to AI collaboration, particularly in
22. 1:07professional environments, such as what
23. 1:10are the implications of working with
24. 1:12this AI? Who might be affected by what
25. 1:14is created or by the collaboration
26. 1:16itself or by any missed
27. 1:19inaccuracies? Who has access to the data
28. 1:21used to produce this output? How do I
29. 1:24ensure that my interaction and the
30. 1:26outcome aligns with ethical standards
31. 1:29and
32. 1:30values? Think about it like driving a
33. 1:32car. We don't just focus on getting from
34. 1:35point A to point B efficiently. We also
35. 1:38consider safety, follow traffic rules,
36. 1:40and remain aware of how our driving
37. 1:42affects others on the road. Similarly,
38. 1:45diligence recognizes that AI systems and
39. 1:48our interactions with them don't exist
40. 1:51in a vacuum. Working with AI responsibly
41. 1:54requires awareness of broader contexts
42. 1:57and their implications. Diligence begins
43. 2:01with becoming more critically thoughtful
44. 2:03about which AI systems we work with, how
45. 2:06we work with them, and the impacts that
46. 2:08come from those collaborations. We
47. 2:10should seek answers to questions like,
48. 2:13how is this system trained and built?
49. 2:15What data was used? Who owns the data
50. 2:18I'm inputting right now? Who may have
51. 2:20access to it once it's shared? How am I
52. 2:23protecting the privacy and security of
53. 2:25myself and others? What other impacts
54. 2:28does this system
55. 2:29have? How does this interaction align
56. 2:32with my personal and professional values
57. 2:34or with my organization's
58. 2:37policies? For example, before sharing
59. 2:40sensitive company information with an AI
60. 2:42assistant, it's important to first check
61. 2:44whether the service has appropriate data
62. 2:46protection policies in place or if your
63. 2:49organization permits such
64. 2:51sharing. We call this type of diligence
65. 2:54creation diligence. It is your ability
66. 2:57to be critical and intentional about
67. 2:59which AI systems you choose to work with
68. 3:01and how you work with
69. 3:04them. Different settings, personal,
70. 3:06academic, creative, and professional may
71. 3:09have different expectations of
72. 3:11disclosure about AI
73. 3:13interaction. However, the responsibility
74. 3:15is on each of us to understand and meet
75. 3:17these
76. 3:18expectations. Ask yourself, who needs to
77. 3:21know about AI's role in this work? How
78. 3:24and when should I communicate this? What
79. 3:26level of detail makes sense to
80. 3:29share? Meeting expectations for
81. 3:31transparency, in other words, being
82. 3:33forthright and honest, isn't just about
83. 3:36following rules and regulations. It's
84. 3:39about maintaining trust and respect in
85. 3:42your
86. 3:43relationships. It acknowledges that
87. 3:44people have the right to know when AI
88. 3:46has played a significant role in content
89. 3:48creation or in decisions that affect
90. 3:50them. For instance, if you used AI to
91. 3:54help draft a team proposal, letting your
92. 3:56colleagues know which parts were AI
93. 3:58assisted allows for a more honest
94. 4:01collaboration and keeps everyone on the
95. 4:03same page. We call this transparency
96. 4:07diligence. It's the ability to be open
97. 4:09and accurate about AI interaction with
98. 4:12everyone who needs to know. As we
99. 4:15discussed before, AI systems can make
100. 4:18mistakes. When you share AI generated
101. 4:21content with the world, you not the AI
102. 4:24are ultimately responsible for its
103. 4:27accuracy and
104. 4:28appropriateness. This means verifying
105. 4:30facts, checking for biases, ensuring
106. 4:34accuracy and usage rights, and other
107. 4:36checks needed so that you can stand
108. 4:38behind what you
109. 4:40share. Consider a journalist who uses AI
110. 4:44to help draft an article. Before
111. 4:47publishing, they would need to verify
112. 4:49every fact and source. Ensure that the
113. 4:52final piece meets every journalistic
114. 4:54standard, the same standards that would
115. 4:56apply had they written it entirely
116. 4:58themselves. We call this deployment
117. 5:01diligence. It's the ability to take
118. 5:04informed responsibility for the outputs
119. 5:06that you use or share after they've been
120. 5:09created with AI assistance. Navigating
121. 5:12these diligence considerations isn't
122. 5:15always straightforward.
123. 5:17Different contexts and stakeholders may
124. 5:19have different expectations and
125. 5:21standards. So it helps to develop
126. 5:24personal guidelines for working with AI
127. 5:27that align with your own ethics and
128. 5:29values. And in professional contexts,
129. 5:32familiarize yourself with organizational
130. 5:34policies and industry
131. 5:36standards. And remember that the legal
132. 5:38and regulatory frameworks around AI are
133. 5:41still emerging and will continue to
134. 5:43evolve.
135. 5:45Staying informed is an important part of
136. 5:48diligence. To
137. 5:50recap, creation, transparency, and
138. 5:53deployment diligence work together to
139. 5:56form the complete diligence competency.
140. 5:59By developing your capacity for
141. 6:01diligence, you ensure that your AI use
142. 6:04is not only effective and efficient, but
143. 6:06also ethical and safe. Diligence reminds
144. 6:10us that our interaction with AI comes
145. 6:12with
146. 6:13responsibilities. To be thoughtful about
147. 6:16the systems we choose and about how we
148. 6:18work with them, to be honest about AI's
149. 6:22role in our work, and ultimately to be
150. 6:25accountable for what we create when
151. 6:28working with
152. 6:29AI. We all want AI that is fair and safe
153. 6:33and of benefit to our society. Our own
154. 6:36behaviors play a key role in making this
155. 6:39happen.