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“Younger workers are struggling, especially in the areas of financial and mental health.

Action Items 🗹 Identify potential areas of concern based on the review process (e.g., data integrity, significant disparate impact, inconsistent human overrides). 🗹 Prioritize findings that pose the highest legal risk or risk to employee trust or equity goals. 🗹 Determine whether specialists (e.g., data scientists, legal guidance, AI vendor team) should be engaged to mitigate significant compliance issues. 🗹 Evaluate minor issues found and suggest remedies (e.g., improved data collection, additional user training). 🗹 Continuously monitor AI tool inputs and outputs for bias issues.

According to Dennison, pay, benefits and advancement is likely a major area where they’ll want to see tangible investment.

Provide reasonable mitigation options, such as ergonomic support, adjustable lighting or proximity to quieter areas.; ;A supportive culture.

Wolf: In what areas do you feel immigration policy changes are impacting employers?

Wellbeing Diagnostic Survey showed financial well-being is the top employee challenge for employers, and also the area in which they believe they’re least effective.

In addition, survey participants cited a wide range of areas for benefits improvement, including: ;Greater financial contributions from their employer (48%);; ;Greater flexibility (34%);; ;More resources around financial well-being (33%); and,; ;Paid time off conversion (31%).; The fact that fewer than half suggested more money suggests “an unfortunate lack of a silver bullet,” Spiegel said.

.; Essential Uses for XAI To build your business case for demanding XAI from your AI systems, consider the following areas where a black-box system could negatively impact an employer.

Justifiable reasons might include a national posting across multiple geographic areas, multi-level postings in which candidates could be slotted into different internal tiers based on their interview performance, or niche postings for emerging or specialized roles.

This may involve including one AI initiative in your annual plan and seeing it through to completion; driving quick wins by focusing on areas that are appreciated by leadership, such as simplification and efficiency; or prioritizing AI initiatives that enable your team to experiment and explore to build their foundational experience for aspirational future projects.