Training a workforce in AI and ML systems is challenging because the subject is complex and requires more than technical training. Image: Gargantiopa / Shutterstock.com
By: FEDweek StaffIn a report whose findings could be applicable to other agencies as well, the IG at Interior has said that “the human capital dimension” is among the challenges the department faces as it tries to incorporate artificial intelligence and machine learning technologies into its operations.
In a survey, the department’s bureaus and offices “stated that they are confronting “fundamental gaps” in their technological readiness. There is a “technological skill gap” that “is particularly evident among technical staff and leadership,” the report said, and “training a workforce in AI and ML systems is challenging because the subject is complex and requires more than technical training.”
There is a need for comprehensive education programs that not only teach technical skills but that also “cultivate an understanding of responsible AI use, ethical considerations, and potential organizational risks. They stated that these programs do not exist at this time within DOI,” it said.
Many of the bureaus further reported “what they called a pronounced absence of comprehensive AI strategies and clear implementation and execution policies” that have left some of them waiting for broader departmental guidance, it said.
In addition, “data management and engineering is emerging as a critical bottleneck, with bureaus struggling to address data challenges. According to the bureaus, these obstacles lie in collecting data as well as in cleansing, standardizing, and preparing datasets to ensure reliable and meaningful AI outcomes. Bureau and office program areas moreover stated that they face challenges in identifying and securing funding for what they termed essential data preparation efforts.”
Beyond such issues, “many of the survey respondents expressed their belief that cultural resistance and a limited understanding of AI’s transformative potential further complicate technological integration, creating a multilayered barrier to effective implementation.”
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