Recruiter's AI Digest #65
Resources and perspectives to keep you ahead of the curve as AI deepens its impact in Recruiting. 🤖
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This week’s digest
Check out the awesome material this week 📖 :
Gen AI: Too Much Spend, Too Little Benefit?
(Goldman Sachs)Lattice makes its AI agents employees
(Glen Cathey)Ethical AI in Recruiting: A Guide for Talent Leaders
(Kevin Wheeler)The Benefits of AI-Assisted Software Development
(Pragmatic Engineer)
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GEN AI: TOO MUCH SPEND, TOO LITTLE BENEFIT?
(Goldman Sachs)
TLDR: Whether you are an AI skeptic or not, spending on it is huge, and it is expected to impact job tasks in a meaningful way (automating up to 25% of tasks).
Tech giants are set to spend over $1 trillion on AI infrastructure in the coming years, with debate on whether this investment will pay off. While some experts are optimistic, others are skeptical about AI's potential economic benefits.
Investment Concerns:
Skepticism: MIT's Daron Acemoglu argues that only a small fraction of tasks will be cost-effective to automate in the next decade, predicting a mere 0.5% increase in US productivity and 0.9% GDP growth from AI.
"Given the focus and architecture of generative AI technology today... transformative changes won’t happen quickly and few—if any—will likely occur within the next 10 years." - Daron Acemoglu, MIT
High Costs: Goldman Sachs' Jim Covello highlights the substantial costs of AI technology, emphasizing that AI must solve complex problems to justify its expense, which it currently doesn't.
"AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do." - Jim Covello, GS
Optimistic Views:
Long-Term Potential: GS senior economist Joseph Briggs believes generative AI will eventually automate 25% of work tasks, raising US productivity by 9% and GDP by 6.1% over the next decade.
Infrastructure Phase: Analysts see current AI spending as a promising investment cycle led by established companies with low capital costs and vast distribution networks.
"Spending is certainly high today in absolute dollar terms. But this capex cycle seems more promising than even previous capex cycles." - Kash Rangan, GS
With AI many changes to roles on the market will come
Historical Evidence: Technology-driven reallocation of resources has historically driven economic growth by creating new tasks and expanding production capabilities.
Impact of AI: AI is expected to raise output by increasing demand in areas where labor has a comparative advantage and by creating new, previously infeasible opportunities.
Examples from IT: The emergence of information technology led to new occupations like webpage designers, software developers, and digital marketing professionals, boosting demand in related service sectors such as healthcare, education, and food services.
Employment Growth: According to MIT economist David Autor, 60% of current occupations did not exist in 1940, with technology-driven creation of new jobs accounting for over 85% of employment growth in the last 80 years.
See graph below….
Read the full report here.
LATTICE MAKES ITS AI AGENTS EMPLOYEES
(Glen Cathey)
TLDR: Some companies are starting to recognise AI agents as employees. Although it’s important that HR takes into account the impact of agents on its employees, treating AI agents as actual employees is questionable.
Lattice recently announced a bold move to treat AI agents as digital workers, onboarding them with official employee records, training, and performance metrics. This announcement sparked significant backlash, prompting Lattice to withdraw the initiative and emphasize the need for responsible AI use.
Glen Cathey laid out his thoughts on the matter….
AI agents, while not human, should involve HR in strategic planning due to their growing impact on work and workforce dynamics:
Task Performance: AI is increasingly capable of performing various tasks and potentially entire jobs, affecting workforce planning and skills development.
HR Processes: AI tools are integral to recruitment, onboarding, and talent management, necessitating HR oversight.
Job Roles and Skills: AI adoption reshapes job roles and required skills across organizations.
Ethical Use: HR must ensure ethical use of AI, particularly in hiring algorithms and related practices.
Employee Experience: AI influences employee engagement and overall experience, central concerns for HR.
Traditional HR frameworks may need to evolve to better integrate AI's unique role and impact on human work. This raises important questions for the future of HR and AI collaboration.
Some good discussion in the comments here
ETHICAL AI IN RECRUITING: A GUIDE FOR TALENT LEADERS
(Kevin Wheeler)
TLDR: Avoidance isn’t a winning approach, but steps can be taken to ensure ethical implementation of AI.
Many recruiting leaders are eager to implement automation and AI into their processes but face a complex landscape of ethical considerations, regulatory compliance, and technological integration. Concerns about privacy, bias, and candidate comfort with AI tools add to the challenge.
Key Concerns:
Privacy and Bias: Fears about data privacy and algorithmic bias are significant, along with concerns about legal implications.
Candidate Comfort: There is worry that candidates may be uncomfortable with tools like chatbots or virtual assessments.
Proactive Approach: Despite these challenges, avoiding or delaying AI integration may be a mistake as AI becomes integral to recruiting products. A proactive, strategic, and carefully planned approach can address these concerns.
Steps for AI Integration:
Identifying Needs:
Assess the organization's needs and technological readiness.
Identify pain points that AI could address, such as efficient resume screening or maintaining candidate communication.
Start small with pilot projects to test AI solutions and identify weaknesses.
Scaling Gradually:
Begin with small-scale implementations, like AI-powered chatbots or resume screening tools.
Refine and tweak tools based on initial results before expanding across the recruiting process.
Team Communication:
Educate the recruiting team about how AI tools work and what to expect.
Reassure recruiters that AI is meant to augment their work, not replace them.
Communicate clearly with all stakeholders about the reasons for and benefits of AI integration.
Ethics and Compliance:
Develop comprehensive AI ethics and privacy policies covering data protection, bias mitigation, transparency, and human oversight.
Clearly communicate how data will be collected, used, and how candidate consent will be obtained.
Provide candidates with explanations of AI use in the selection process and options to opt out of AI-assisted evaluations.
THE BENEFITS OF AI-ASSISTED SOFTWARE DEVELOPMENT
(Pragmatic Engineer)
TLDR: Software developers are finding tangible efficiency gains through implementing AI into their day to day workflows.
Over 200 developers shared their experiences with AI-assisted software development, highlighting several genuinely helpful use cases.
Massive Help in Completing Projects:
AI tools have been a huge help in converting Linux-specific bash scripts to cross-platform Python3 scripts that also work on Windows, making the transition seamless and efficient.
Improved Testing and Code Quality:
Developers reported better use of test cases and improved overall code quality. A web developer with 7 years of experience noted, "We are seeing better use of test cases, better code quality, and better documentation. This is true both at the individual and team level."
Educational Benefits:
AI assists tech workers in learning new technologies and frameworks faster and in a more interactive way. Many respondents shared that LLMs have been instrumental in helping them get up to speed with new frameworks quickly.
Easier Prototyping and Experimentation:
Building prototype versions of products has become much simpler and faster with AI assistance. One respondent mentioned, "Prototyping new features has become a breeze with AI tools, allowing us to experiment more freely."
Enhanced Documentation and Communication:
AI tools like Notion AI have boosted the quality of documentation, reviewed documents, and helped find relevant information efficiently. "AI has significantly improved our documentation quality, making it easier for teams to communicate and stay on the same page," noted another developer.
Workflow improvements:
85% of respondents reported that AI tools had a positive impact on their workflow, highlighting how AI-powered coding assistance and debugging tools have streamlined their development processes.
While there are downsides, such as poor output and over-reliance on these tools, the benefits of AI in software development are undeniable for those in the field.
You can see the post here.
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