Serendipity35

I saw the quote pictured above that goes back to 1979 when artificial intelligence wasn't part of the conversation. "A computer must never make a management decision," said an internal document at the big computer player of that time, IBM. The why of that statement is because a computer can't be held accountable.

Is the same thing true concerning artificial intelligence 46 years later?

I suspect that AI is currently being used by management to analyze data, identify trends, and even offer recommendations. But I sense there is still the feeling that it should complement, not replace, human leadership.

Why should AI be trusted in a limited way on certain aspects of decision-making?

One reason that goes back at least 46 years is that it lacks "emotional intelligence." Emotional intelligence (EI or EQ) is about balancing emotions and reasoning to make thoughtful decisions, foster meaningful relationships, and navigate social complexities. Management decisions often require a deep understanding of human emotions, workplace dynamics, and ethical considerations — all things AI can't fully grasp or replicate.

Because AI relies on data and patterns and human management often involves unique situations where there might not be clear precedents or data points, many decisions require creativity and empathy.

Considering that 1979 statement, since management decisions can have far-reaching consequences, humans are ultimately accountable for these decisions. Relying on AI alone could raise questions about responsibility when things go wrong. Who is responsible - the person who used the AI, trained the AI or the AI itself? Obviously, we can't reprimand or fire AI, though we could change the AI we use, and revisions can be made to the AI itself to correct for whatever went wrong.

AI systems can unintentionally inherit biases from the data they're trained on. Without proper oversight, this could lead to unfair or unethical decisions. Of course, bias is a part of human decisions and management too.

Management at some levels involves setting long-term visions and values for an organization. THis goes beyond the realm of pure logic and data, requiring imagination, purpose, and human judgment.

So, can AI handle any management decisions in 2025? I asked several AI chatbots that question. (Realizing that AI might have a bias in favor of AI.) Here is a summary of the possibilities given:

Resource Allocation: AI can optimize workflows, assign resources, and balance workloads based on performance metrics and project timelines.

Hiring and Recruitment: AI tools can screen résumés, rank candidates, and even conduct initial video interviews by analyzing speech patterns and keywords.

Performance Analysis: By processing large datasets, AI can identify performance trends, suggest areas for improvement, and even predict future outcomes.

Financial Decisions: AI systems can create accurate budget forecasts, detect anomalies in spending, and provide investment recommendations based on market trends.

Inventory and Supply Chain: AI can track inventory levels, predict demand, and suggest restocking schedules to reduce waste and costs.

Customer Management: AI chatbots and recommendation engines can handle customer queries, analyze satisfaction levels, and identify patterns in customer feedback.

Risk Assessment: AI can evaluate risks associated with projects, contracts, or business decisions by analyzing historical data and current market conditions.

As I write this in March 2025, the news is full of stories of DOGE and Elon Musk's team using AI for things like reviewing email responses from employees, and wanting to use more AI to replace workers and "improve efficiency."  AI for management is an area that will be more and more in the news and will be a controversial topic for years to come. I won't be around in another 46 years to write the next article about this, but I have the feeling that the question of whether or not AI belongs in management may be a moot point by then.

The term FOBO appeared in something I was reading recently. It is the fear of becoming obsolete (FOBO) and it is very much a workplace fear and generally connected to aging workers and anyone who fears that they will be replaced by technology.

Of course, AI is a large part of this fear. It's not a new fear. Workers have always considered that they would be considered obsolete as they aged, especially if they did not have the skills that younger employees brought to the workplace. It has been at least two decades of hearing predictions that robots would replace workers. In fact, that was the case, though not to the levels that were sometimes predicted. Artificial intelligence is less obvious as it makes inroads into our work and outside life.

Employers and workers need to be better at recognizing the ways AI is already here and being used. Approximately four in ten Americans use Face ID to log into at least one app on their phone each day. That is about 136 million people. How many think about that as AI?

If you have an electric vehicle, A.I.-powered systems work to manage the energy output. In your gas-powered car, you very likely use an AI-powered GPS for navigation.  

One survey I saw found that just 44 percent of the global workforce believe they interact today with AI in their personal lives. But when asked if they used GPS maps and navigation, 66 percent said yes. What about predictive product/entertainment suggestions, such as in Netflix and Spotify?  50 percent said yes.  Do you use text editors or autocorrect? A yes from 47 percent. 46 percent use virtual home assistants, such as Alexa and Google Assistant. Even chatbots like ChatGPT and CoPilot - which are less hidden and more proactive for a user - had a 31 percent yes response.

Most of these are viewed as positive uses of AI, but not all uses are viewed as positive or at least are viewed as somewhat negative. One example of that category is the AI not so positive is its use in filling up newsfeeds. Each social media network - Facebook, Twitter, Instagram et al  - has its own A.I.-powered algorithm. It is constantly customizing billions of users’ feeds. You click a like button, or just pause on a post for more than a few seconds,and that information changes your feed accordingly. Plus, the algorithm is made to push certain things to users that were not suggested by your activity but by sponsors or owners. This aspect has been widely criticized since Elon Musk took over Twitter-X, but all the platforms do it to some degree.

Some common applications are both positive and negative. Take the use of artificial intelligence in airports all over the world. It is being used to screen passengers passing through security checkpoints. At least 25 airports across the U.S., including Reagan National in Washington D.C. and Los Angeles International Airport, have started using A.I.-driven facial recognition as part of a pilot project. Eventually, the Transportation Security Administration (TSA) plans to expand the ID verification technology to more than 400 airports. This can speed up your passage through security which is something everyone would love to see, but what else is being done with that data, and will the algorithm flag people for the wrong reasons?

Do you want to push back on FOBO, particularly in the workplace? Some suggestions:
Continuous Learning: Stay curious and keep updating your skills. Whether it’s taking a course, attending workshops, or learning new technologies, continuous education is key.
Networking: Engage with your professional community. Networking can provide insights into industry trends and offer support and advice.
Adaptability: Embrace change and be open to new ideas. Flexibility can help you stay relevant.
Mindset Shift: Focus on your unique strengths and contributions. Everyone has something valuable to offer, and feeling obsolete often stems from undervaluing your skills.
Digital Detox: Sometimes, limiting your exposure to social media and other sources of comparison can reduce feelings of inadequacy.
Seek Feedback: Regularly seek feedback from peers, mentors, and colleagues to understand your areas of improvement and strengths.

After retirement, some older workers are turning to gig work to keep busy and sharp, as a lifeline, or as a last resort. So reports Rest of World who spoke to 50 older workers worldwide.

Most gig workers globally are relatively young: Research published in 2021 by the International Labour Organization (ILO), a United Nations agency focused on improving working conditions, puts the average age for delivery workers at 29 and the average age for ride-hailing drivers at 36. But older individuals are turning to gig work, and their numbers are expected to grow in the coming years.

For example, a man in São Paulo drives people at least 12 hours a day, and at 62, he doesn’t see himself stopping anytime soon. He makes roughly 4000 reais ($790) per month after paying off all expenses; it is now his household’s only income. In a country where the monthly minimum wage is 1,412 reais ($273), it’s a good income.

I wrote about gig work and "unretirement" on this blog five years ago, and started writing about it 9 years ago on another blog when I decided to do it myself.

The global population of people 65 or older is expected to double by 2050, surpassing 1.6 billion, according to the U.N. At the same time, family units worldwide are transforming, often requiring older people to support themselves for longer. Not all gig workers do it full-time, and for many people (especially younger workers) it supplements other work.

In America, things are different but the trend is still evident. Over the last two decades, the share of the workforce aged 55 or older almost doubled and the government is looking at labor trends like this. By 2028, over a quarter of the workforce will be 55 or older. Inflation has been a factor in forcing retirees back to work. 43 percent of those considering returning to work are doing so because of inflation. One report identifies that older Americans are increasingly turning to the gig economy to supplement their incomes and savings due to its flexibility. Nearly 1 in 3 independent or “gig” workers are over age 55.

When I was teaching in a high school, I used to tell students (and faculty) that we were not preparing them for jobs. I was sure many of our students would end up in jobs with titles that did not exist then. There is a song by The Byrds from the 1960s titled "So You Wanna Be a Rock 'n' Roll Star." In 2024, it could be "So You Want To Be An AI Prompt Engineer."

The role of AI prompt engineer attracted attention for its high-six-figure salaries when it emerged in early 2023. What does this job entail? The principal aim is to help a company integrate AI into its operations. Some people describe the job as more prompter than engineer.

There are already tools that work with apps like OpenAI’s ChatGPT platform that can automate the writing process using sets of built-in prompts. Does that mean that AI will replace AI prompt engineers already? For now, the prompter works to ensure that users get the desired results. They might also be the instructors for other employees on how to use generative AI tools. They become the AI support team. AI can automate "trivial" tasks and make more time for work that requires creative thinking.

What kind of training leads to getting this job? You might think a background in computer science, but probably a strong language and writing ability is more important. People who write in the corporate world might justifiably fear AI will take their jobs away. Being a prompter might be an alternative.

Still, I suspect that there is a good possibility that a prompter/engineer's job might be vulnerable as software becomes better at understanding users’ prompts.

If you are interested in being an AI prompt engineer, I posted last week about some free online courses offered by universities and tech companies that included three courses that relate to creating prompts for AI.

AI Applications and Prompt Engineering is an edX introductory course on prompt engineering that starts with the basics and ends with creating your applications.

Prompt Engineering for ChatGPT is a specific 6-module course from Vanderbilt University (through Coursera) that offers beginners a starting point for writing better prompts.

Another course on ChatGPT Prompt Engineering for Developers is offered by OpenAI in collab with DeepLearning and it is taught by Isa Fulford and Andrew Ng.  It covers best practices and includes hands-on practice.