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I L T A N E T . O R G
DEI initiatives should strive to achieve end goals.
However, moving the needle on DEI efforts looks like
progress rather than victory. It is vital to celebrate
incremental progress instead of focusing on completing
a final outcome. AI that uses high-quality data can help
the legal industry gauge progress toward DEI goals.
Encouraging participation requires intentional outreach
and communication to improve the data pool. To achieve
this, organizations must clarify that every voice matters
and ensure that insights gained from data collection
efforts will drive meaningful change. Effectiveness
in this type of data collection involves recruiting
underrepresented groups as active participants and
increasing the accessibility and inclusivity of the data
The quality of insights and conclusions we gather from
analyzing any data set directly reflects the quality and
comprehensiveness of the data collected. Like other
tools and technologies, AI works with the data it ingests.
The AI tool's work quality reflects the data it receives.
For example, large language models (LLMs) are built
on massive datasets and generate responses based
on patterns and knowledge they have been trained on.
However, if the data fed into these models is incomplete,
biased, or inaccurate, the output will reflect those
deficiencies. Ensuring data quality is a weakness of AI,
however advanced it may be. Since understanding diverse
populations' experiences, challenges, and needs is vital to
DEI, having accurate and actionable data is essential.
READ MORE
ONLINE
find this recent DEI
article from the Fall
2024 issue of Peer to
Peer Magazine.
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