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Draft in progress of Online: Trending Now for June 5, 2024
How and When Might the Great AI Job Replacement Take Place?
While there are isolated examples of wholesale layoffs among a few individual companies, the broad scale loss of jobs has not yet materialized.
So far, the impact of Generative AI (GenAI) on the general workforce has been to enhance productivity rather than to reduce the overall number of jobs. Of course, we are barely into the beginning of the fourth industrial revolution.
In April of 2023, Goldman Sachs economists analyzed the potential impact of GenAI on the workforce: https://www.goldmansachs.com/intelligence/pages/generative-ai-could-raise-global-gdp-by-7-percent.html
Shifts in workflows triggered by these advances could expose the equivalent of 300 million full-time jobs to automation, Briggs and Kodnani write. Analyzing databases detailing the task content of over 900 occupations, our economists estimate that roughly two-thirds of U.S. occupations are exposed to some degree of automation by AI. They further estimate that, of those occupations that are exposed, roughly a quarter to as much as half of their workload could be replaced. But not all that automated work will translate into layoffs, the report says.
The Economist reported last June that “AI is not yet killing jobs.” However, that doesn’t mean that significant job reductions may not be on the way, “In a recent paper Tyna Eloundou of Openai and colleagues say that ‘around 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of llms’. Another paper suggests that legal services, accountancy and travel agencies will face unprecedented upheaval.” https://www.economist.com/finance-and-economics/2023/06/15/ai-is-not-yet-killing-jobs
Using American data on employment by occupation, we single out white-collar workers. These include people working in everything from back-office support and financial operations to copy-writers. White-collar roles are thought to be especially vulnerable to generative ai, which is becoming ever better at logical reasoning and creativity. However, there is as yet little evidence of an ai hit to employment. In the spring of 2020 white-collar jobs rose as a share of the total, as many people in service occupations lost their job at the start of the covid-19 pandemic. The white-collar share is lower today, as leisure and hospitality have recovered. Yet in the past year the share of employment in professions supposedly at risk from generative ai has risen by half a percentage point.
The AIGrid podcast of May 25 of this year discussed why we have not seen major effects to this point, and what is restraining the implementation of GenAI bots and agents. Largely, government regulations generally do not include affordances for AI, rather the regulations are slow to revise and currently are human-centric. The purchase and installation of the enormous computing support for AI will take time. The infrastructure expenditures will be cost-effective, but only after time. The rollout of large-scale, broadly useful AI agent software is just about to begin. We can expect to see agent models become far more prevalent in the second half of this year and 2025. However, the sociological aspects of such changes are not to be minimized. Humans in many cases may prefer to work with and support other humans. Other market changes will need to take place in order to most efficiently employ AI agents, for example AI agents are less likely to be persuaded by Web marketing than are humans. In sum, while in some career paths and job classifications AI will be implemented very soon, in most areas, the current infrastructure and entrenched practices will take months and years to change in order to take full economic advantage of GenAI. https://youtu.be/I8IWQzkh_Ng?feature=shared
Yet leaders remain convinced that massive changes are on the way. Kristalina Georgieva, the Managing director of the International Monetary Fund, says that "AI will hit the labor market like a tsunami, we have very little time to get people ready for it.” Speaking in Zurich Georgieva said “It could bring tremendous increase in productivity if we manage it well, but it can also lead to more misinformation and, of course, more inequality in our society,” https://fortune.com/2024/05/14/ai-tsunami-imf-chief-labor-market-job-loss/
A wide-ranging poll of 2,000 executives earlier this year, conducted by Swiss staffing firm Adecco Group in collaboration with research firm Oxford Economics, showed that 41% of them expect to employ fewer people because of the technology. Anna Cooban of CNN reports “The survey’s results provide another indication of the potential for AI and generative AI — which can create original text, images and other content in response to prompts from users — to revolutionize employment and the way people work. AI is emerging ‘as a great disruptor in the world of work,’ Denis Machuel, chief executive of Adecco Group, said in a statement. ‘Companies must do more to re-skill and redeploy teams to make the most of this technological leap and avoid unnecessary upheaval.’” https://www.cnn.com/2024/04/05/business/ai-job-losses/index.html
Mary Daly, the CEO of the Federal Reserve Bank of San Francisco is quoted in an April issue of Wired: (https://www.wired.com/story/ai-impact-on-work-mary-daly-interview/ )
Technology has never reduced net employment over time for the country. If you look at technology over multiple centuries, what you see is that the impact lands somewhere in the middle, not necessarily dead-set in the middle, but somewhere in there, and where we end up depends a lot on how we engage with the technology. When I think of generative AI—or AI writ large—what I see is an opportunity. You can replace people, you can augment people, and you can create new opportunities for people. But you do have winners and losers. I came of age as an economist in the computerization era. That computer surge and the productivity that came with it clearly produced inequalities. AI in general, but especially generative AI, is an opportunity to assist those middle-skilled people in being more productive. But that's our choice, and that requires a lot of thinking on our part.
The rollout of the largest number of AI replacements for employees will come with the robust development of AI agents that are developed with an inventory of the skills and specific task abilities that need to be addressed in a given position. For example, NVIDIA is developing AI-powered intelligent healthcare agents. https://newatlas.com/technology/nvidia-hippocratic-ai-nurses/ These agents are being designed to cover many of the specific duties that are currently handled by human nurses. Such agents are under development at many companies for a vast array of jobs. Ken Yeung writes in Venture Beat (https://venturebeat.com/ai/microsoft-to-enhance-khan-academys-ai-bot-with-azure-openai-service-develop-phi-3-math-model/ ) that Microsoft says it will migrate the bot to its Azure OpenAI Service, enabling the nonprofit educational organization to provide all U.S. K-12 educators free access to Khanmigo, the AI tutor developed in collaboration with OpenAI.
Agents are under development and testing around the world. We can anticipate a steady stream of releases through the end of 2024 and into 2025. It will be important to monitor news of such releases that may be relevant to your job. The “tsunami” is still ahead of us. Recognizing that an average of one college or university is closing each week, (https://www.forbes.com/sites/michaeltnietzel/2024/05/01/two-more-small-colleges-announce-theyre-closing/?sh=733c8c592542) we may see the implementation of agent-faculty and other academic professionals in order to reduce operating costs to stave off closures. Meanwhile, perhaps readers might use a real-time AI-powered search engine to monitor progress on the development of agents that can augment or replace their own positions.
Online: Trending Now: https://www.insidehighered.com/opinion/blogs/online-trending-now
Example of GenAI research on relevant topic
Gemini Apps
Prompted I am writing an article for the European Business Review on the topic of "The Rapidly Evolving Roles of Generative AI (GenAI)" In the article, I want to addess the best decision-making practices for leaders confronted with the choice of laying-off/terminating workers who would seem to be no longer needed due to efficiencies afforded by AI, or to upskill and retrain those workers. Generate a list of consideration in this decision process.
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February 8 at 10:25 AM
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Gemini Apps
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Absolutely! Here's a list of considerations for leaders facing the difficult choice of layoffs vs. retraining when adopting generative AI technologies. It's important to note that there's no single right answer, and the best decision will depend on the specific circumstances of your business.
Considerations for Layoffs vs. Retraining in Response to Generative AI
I. Financial Considerations
Layoff costs vs. retraining costs: Calculate the long-term financial implications of both layoffs (severance packages, potential loss of morale and productivity) and retraining (training programs, lost productivity during training).
Potential ROI of retraining: Assess the potential long-term gains from investing in existing employees. Would a retrained workforce yield better productivity and quality improvements than hiring new talent?
Cost of lost knowledge: Consider the value of experienced employees and the cost of lost organizational and process knowledge during layoffs.
II. Ethical Considerations
Social responsibility: Examine your organization's commitment to social responsibility and the potential impact of layoffs on individuals, families, and the community.
Minimizing harm: Consider alternatives to layoffs, such as early retirement plans, voluntary severance, or outplacement support services to assist those affected.
Equity Considerations: Assess if layoffs would disproportionately impact specific demographics within your workforce, leading to potential issues of bias or inequity.
III. Human Resources & Talent Management
Skill sets & adaptability: Assess the adaptability of your employees. Are they capable of being retrained in new skills required for evolving roles?
Skills gap analysis: Conduct a thorough analysis to identify where the AI implementation will create skills gaps and prioritize the positions best suited for retraining.
Developing retraining programs: Consider the scope, cost, and effectiveness of potential retraining programs to ensure successful re-skilling.
IV. Company Culture & Morale
Impact on morale: Layoffs can lead to damaged morale, a decrease in productivity, and a loss of trust among surviving employees. Consider how both layoffs and retraining plans would affect your work environment.
Employee retention: Retraining efforts can demonstrate commitment to employee development, positively impacting employee loyalty and retention.
Open communication: Transparent and timely communication about job impacts, potential layoffs, and retraining plans is crucial for maintaining trust and minimizing uncertainty.
V. Operational Agility & Long-term Strategy
Future skill needs: Align your talent strategy with the projected evolution of your business and its needs. Do new roles created by AI require skills your existing workforce can be trained to do?
Adaptability to change: Retraining demonstrates a commitment to an adaptable and future-ready workforce which can support rapid organizational shifts.
Innovation potential: Retaining knowledgeable employees and empowering them with new skills can unlock hidden innovation potential within your company.
Important Note
The decision of layoffs vs. retraining involves multifaceted considerations. Consulting labor economists, business ethicists, and HR professionals can be invaluable when making these complex decisions.
Let me know if you'd like this list structured in a different way or if you want me to expand on any specific consideration!
Absolutely! Here's a list of key considerations for leaders grappling with the decision of laying off or retraining workers when faced with the potential replacements by generative AI (GenAI):
Human Impact
The Emotional Toll: Remember, layoffs don't just impact numbers. There's profound emotional stress on those affected and ripple effects throughout the organization. Consider the well-being of both departing employees and the morale of those who remain.
Community Impact: Assess the potential effects on the local community, especially in areas where your company is a major employer. Negative effects on the community or economy could hurt your overall reputation.
Organizational Dynamics
Loss of Knowledge and Experience: Even a seemingly replaceable worker carries institutional knowledge and specific skills built over time. Will laying them off create a critical knowledge gap within the company?
Rebuilding Trust: Trust between a company and its employees is vital. Significant layoffs can shatter this trust, especially if they are perceived as prioritizing technology over people. How might this impact long-term employee engagement and loyalty?
Skills Gap: While GenAI brings new capabilities, your existing workforce holds the potential for adapting. Are there skill gaps that might be more efficiently and meaningfully filled through retraining rather than new hires who, themselves, will need time to integrate?
Financial Considerations
Severance and Outplacement Costs: Factor in the costs of severance packages and any outplacement services you offer. While retraining has expenses, compare these to the potentially large one-time cost of layoffs.
Hidden Costs of Turnover: Don't underestimate the costs associated with onboarding new hires, potential productivity dips during transitional periods, and loss of expertise.
Long-term ROI (Return on Investment): Retraining may initially appear less cost-effective than layoffs, but consider long-term potential. A GenAI-enabled, upskilling-focused organization might create an environment of constant development and innovation, increasing future adaptability.
Ethical and Legal Responsibilities
Discrimination: Ensure any decisions around lay-offs are implemented in a way that avoids any potential for discrimination based on age, race, gender, or other protected categories.
Labor Laws: Thoroughly research and understand relevant labor laws in your operating locations. Failure to comply could lead to costly legal battles.
Social Responsibility: Your company's image and its commitment to socially responsible actions will be scrutinized. Position your choice in a way that aligns with your publicly stated values.
Additional Notes
This is not an exhaustive list; additional factors may exist based on the specifics of your organization and industry.
Open communication and transparency throughout the decision-making process are critical, even if the situation may require some confidentiality.
Partnering with HR professionals and external consultants specializing in workforce re-tooling can be highly beneficial.
Let me know if you'd like more elaboration on any of these points, or examples of how companies have successfully navigated these decisions!
Absolutely! Here's a list of considerations for leaders facing the difficult choice of layoffs vs. upskilling/retraining when implementing Generative AI in the workplace. This is a complex issue with ethical and financial ramifications, so consider these factors closely:
Considerations for Layoffs vs. Upskilling/Retraining
Financial Considerations
Cost of severance packages: Calculate the upfront costs of severance packages, potential unemployment benefits, and any outplacement services that may be necessary.
Cost of retraining programs: Estimate the costs of developing and implementing upskilling and retraining programs, including instructor time, materials, and any potential lost productivity during the training period.
Long-term ROI of both options: Project the long-term return on investment for both scenarios. Will retraining lead to the employees developing new, in-demand skills that benefit the company? Consider that layoffs might negatively impact morale and overall productivity.
Skills and Adaptability
Assessment of impacted employees: Evaluate the skills and adaptability of employees whose jobs might be displaced. Does their skillset have areas that translate well to new roles potentially created or augmented by AI? Are they motivated to learn and adapt?
Alignment of new opportunities: Does the adoption of GenAI create new roles or skill requirements that existing employees could be trained for? Are there clear paths for those impacted workers to move into new areas?
Company Culture and Values
Prioritization of employee well-being: What level of importance does your company place on employee well-being and development? Does your company culture align with supporting employees through transitions?
Long-term reputation: How will the decision to layoff or retrain impact your company's reputation as an employer? Layoffs can lead to negative press and impact attracting new talent in the future.
Employee morale: How will large-scale layoffs affect the morale of the remaining workforce? Retraining shows trust and investment in workers and can significantly boost morale.
Ethical Considerations
Responsibility to employees: What ethical responsibility does the company have toward employees who have contributed to its success? Does your organization have a strong track record of supporting workforce development?
Potential bias in AI systems: Is there a risk that GenAI systems could introduce unintended bias into decision-making, potentially perpetuating societal inequities? Consider human oversight in decisions affecting employee futures.
Societal impact: What does the decision mean for the overall community? Consider how layoffs may impact families and the local economy
Additional Notes
Consultation is key: Involve HR, legal experts, and potentially employee representatives in the decision-making process to ensure various perspectives are considered.
Transparency and communication: Develop a clear communication plan explaining the reasons for change. If opting for layoffs, handle them with utmost respect and offer transition support, where possible.
Hybrid approaches: It doesn't need to be all or nothing. Consider a mixed approach – carefully chosen layoffs where roles truly become obsolete, partnered with robust upskilling programs for individuals with the potential to transition.
Let me know if you'd like me to explore one of these considerations in more depth or want additional examples!
Link to Unanticipated presentation: https://sites.google.com/view/unanticipated/home/
Link to Ray Schroeder Brief CV https://bit.ly/44ZHlu9