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Is using AI to apply for jobs cheating, or is it simply the new way candidates prepare?
In this episode, I sit down with Ken Glover, President and Managing Partner of Human Edge Executive Search, to talk about one of the biggest questions showing up in recruitment right now: Can AI help you get hired, or is it crossing an ethical line?
We talk about how candidates are using AI to write resumes, tailor cover letters, prepare for interviews, and organize their experience using tools like the STAR method. But we also dig into the real concern for recruiters and employers: what happens when AI moves from helping someone communicate clearly to helping them misrepresent their skills, experience, or judgment?
Ken shares his perspective from the executive search world on where AI can be a helpful tool, where it becomes a red flag, and why the human element in hiring still matters so much.
Discussion with AI governance experts analyzed Bill 194’s public sector implications with the need for explainable AI and skill development.
Bill 194 and Public Sector
Analysis of Bill 194 indicated that the public sector accepted the regulations but needs resources to adhere to them, emphasizing the elevated need for explainable AI. The legislation places pressure on teams to understand model operations and manage shadow AI sprawl within public sector operations.
Addressing Skill Gaps and Governance
The massive skill shortage, especially in the public sector, requires shifting AI from an IT issue to a governance concern that affects insurance and council matters. Small municipalities should map existing processes to identify automation opportunities and consider collaboration with other small municipalities to sustain AI models.
Policy Integration and Hyperscaler Influence
Integrating AI elements into existing conduct and privacy policies is more beneficial than creating standalone AI policies, supported by investing in AI drills and tabletop exercises. Concern exists that large hyperscalers are developing the AI constitution, which may dictate future government AI policies to support their products and economic interests.
Details
● Introduction and Context Setting: Daphne Thomson and Ali Abbas began the meeting with an informal check-in, noting that Ali made time for the meeting despite travel plans [i]. Daphne explained their work involves implementing practical AI for local governments, focusing on the practical aspects and high-level training [i]. They intended to generate additional content and information for these governmental bodies through their discussion [i].
● Discussion Agenda and Scope: Daphne outlined the agenda, which included discussing Bill 194 and its differences and implications for Ontario, Quebec, and other provinces [i, j]. Other topics included looking at privacy legislation changes in Alberta, the importance of policy, and the ongoing conversation surrounding an AI constitution [i, j]. The plan was to have a 20-minute, informal chat about what is happening in AI within the governance and security domains [i, j].
● Speaker Introductions: Ali Abbas confirmed that they prefer to be called Ali Herji and suggested their role be kept specific to teaching masters-level AI courses at UFRE [i]. Daphne introduced Ali as a former professor from their MBA program in artificial intelligence, emphasizing Ali's expertise and the positive impact of their classes [i, j]. Ali expressed appreciation for the introduction, noting that the engagement with Daphne in class was a pleasure and that they learned a lot from their submissions [i].
● Analysis of Bill 194 and its Impact: Ali explained that provincial legislation regarding AI, such as Bill 194, is not unique to Ontario or Quebec, as every place touched by digitalization is discussing policies for AI control [i, j]. They noted that the bill is specific to the public sector, and the sector's response was not resistance, but rather a request for the necessary resources to adhere to the regulations [i, j]. They advised that the need for human and specialist resources in AI will increase as entities recognize the need for positions like a Chief AI Officer [i].
● The Pressure of Explainable AI and Sprawl: Bill 194 elevates the need for explainable AI, requiring a strong grip on how models operate and transparency regarding their generative outputs and decisions [i]. This legislation places pressure on executive teams and engineers to understand their models and may lead to a rethink of some AI deployments, moving away from viewing AI as a "black box" [i]. Furthermore, organizations must develop a clear declaration of where AI is being used in public sector operations, anticipating the growing challenge of controlling "shadow AI" and AI sprawl [i, j].
● Challenges of Skill Shortage and Governance in Public Sector AI: Daphne observed that while new expertise is needed to implement governance frameworks, there is currently a massive skill shortage, particularly in the public sector where IT staff often focus only on cyber security and hardware [i, j]. AI is becoming a governance issue that extends beyond the IT department to council, affecting aspects like insurance requirements for good governance [i, j]. The practical challenge lies in creating attainable, tiered governance frameworks so that small local governments can benefit from AI without being punished by overly complex requirements from large consulting firms [i].
● Addressing Skill Gaps and Practical Implementation in Smaller Municipalities: Ali countered the idea of an AI professional shortage by stating there is a shortage of AI professionals who can articulate the return on investment and innovation, explaining that many can deploy "amazing things" but struggle to integrate them into workflows [i, j]. Ali advised small municipalities to start by completely reviewing and mapping out all existing processes, data flow diagrams, and standard operating procedures to identify automation opportunities [i, j]. It is critical to determine the true costs—including hosting and token costs—to ensure that AI deployment is financially sustainable, as simply using AI "for AI's sake" may not be worthwhile or cost-effective [i, j].
● Strategy of Collaboration for Smaller Municipalities: Ali noted that a viable strategy for smaller municipalities facing financial constraints is collaboration with associations of other small municipalities, citing past examples of shared services like cyber insurance [i, j]. If smaller municipalities operate as "lone islands," their AI models may not be sustained in the long run unless there is substantial growth in their tax base [i, j]. Daphne agreed that immediate, small wins are possible within existing systems, such as the Microsoft environment, and caution must be used to avoid disastrous results from implementing AI without considering adoption and usage [i, j].
● Integrating AI Policy into Existing Governance: Daphne suggested that instead of creating a standalone AI policy, it would be more beneficial to integrate AI elements into existing policies, such as those governing conduct, IT, and privacy [i, j]. This approach would help address issues like employees not taking responsibility for AI-generated outcomes (e.g., using ChatGPT or Co-Pilot without editing) and embedding AI responsibilities into established organizational workflows [i, j].
● Importance of Practical Training and AI Drills: Ali agreed with the need for integrated policy and emphasized that organizations must invest in tabletop exercises and AI drills, similar to fire drills, to help teams understand the repercussions of unchecked AI output [i, j]. The goal of these engagement strategies is to immerse people in scenarios, making the training engaging and gamified, rather than relying solely on policy to prevent teams from bypassing security measures [i, j].
● The Role of the AI Constitution and Hyperscalers: The discussion shifted to the AI constitution, which private sector companies like Perplexity and OpenAI are developing without government involvement [i]. Ali expressed concern that the influence of large hypersc...
Daphne Thomson introduced Sean Carlson of Melhaney to discuss the environmental effects of AI and sustainability, noting the concern that AI's rapid pace of change poses challenges in understanding its full impact, particularly concerning data center water consumption.
The discussion explored balanced solutions, such as repurposing decommissioned industrial sites, like old pulp mills, into data centers on brownfield sites to offset environmental damage and utilize existing infrastructure.
Sean Carlson and Daphne Thomson highlighted that local governments must proactively ask critical questions about existing utilities, waste streams (like heat and light pollution), and decommissioning plans to mitigate risks and avoid negative legacy issues associated with past industries.
Daphne Thomson and James Moller discussed the integration of AI in HR and recruitment, focusing on AI as an efficiency tool that supports human judgment in tasks like resume screening, data analysis, and summarizing documents.
Moller noted that AI fluency is a crucial skill, and while AI enhances human thinking and handles routine administrative tasks, human oversight is necessary for final decisions on disciplinary matters or hiring selections.
They also addressed organizational AI adoption, policy alignment to mitigate bias, and the continued necessity of critical thinking skills when interacting with AI.Sor
Daphne Thomson and Scott Parker discussed the use and dangers of AI in providing legal advice, agreeing that while AI is useful for summarizing information and drafting, reliance on open AI systems carries a high risk of errors, incompleteness, and hallucinations, with serious consequences for legal matters or municipal bylaw drafting.
Scott Parker emphasized the necessity of human expertise, particularly from experienced peers or lawyers, for oversight and reviewing AI-generated content, noting that legal professionals are trained to interpret complex legislation and case law.
Both stressed the importance of establishing a professional relationship with a lawyer early to facilitate the efficient and comprehensive review of AI-assisted drafts, highlighting that even with client research, lawyers must conduct their own due diligence to ensure legally sound outcomes.
AI is already part of the election landscape, whether we name it or not.
In this recorded webinar Daphne Thomson leads a practical conversation on how artificial intelligence can support local government election teams heading into the 2026 cycle. This session is grounded in real municipal work, not theory.
The discussion covers what AI actually is and what it is not, common misconceptions, and why human accountability always remains central. Daphne walks through how AI can be used responsibly to support election planning, from building compliant work plans and timelines, to drafting statutory notices, supporting budgeting, and organizing nomination intake.
Julie Rogers, APR, and Daphne Thomson discussed the role of AI in communications, emphasizing that while AI speeds up work and generates drafts, it cannot replace the human element of understanding context, tone, and audience.
They highlighted AI's utility in crisis communications, report writing, language simplification, and sentiment analysis, particularly benefiting smaller communities with limited staff.
Both speakers stressed the importance of human oversight, policy, and training to ensure authenticity, maintain public trust, and manage the ultimate responsibility for AI-generated content.
Megan Chorlton of the Municipal Insurance Association of British Columbia (MIA BC) explained that MIA BC provides various insurance coverages to local government members and focuses on stable costs and risk management expertise.
Daphne Thomson and Megan Chorlton discussed the importance of a clear AI use policy, emphasizing flexibility, transparency, human oversight, and awareness of AI biases.
Megan Chorlton affirmed that MIA BC provides ongoing risk management training and resources for AI, including cyber insurance and liability policies that cover some AI-related risks.
During the meeting, Alanna Burton and Daphne Thomson discussed the potential of AI in emergency management, using the Mount Underwood wildfire as a case study.
They highlighted how AI could enhance traditional Emergency Operations Centers by improving information gathering, predictive modeling, post-incident analysis, and public communication.
Alanna Burton and Daphne Thomson emphasized that AI would act as a co-pilot, augmenting human decision-making and automating processes like incident summaries and misinformation countermeasures.
Kent Waugh, founder of the W Group, discussed their services in helping municipal governments build public trust, while Daphne Thomson highlighted how AI can enhance efficiency and capacity in public engagement by quickly extracting key information and facilitating faster decision-making.
Both speakers stressed the importance of human oversight, ethical AI use, transparency regarding AI platforms and prompts, and the need for municipalities to consider community-specific factors and avoid relying solely on social media for public opinion.
Kent Waugh and Daphne Thomson concluded that building trust is achieved through direct, consistent, and clear communication, facilitated by AI, rather than overtly promoting AI itself.
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