by Stacey Lett, Director of Operations, Eastern U.S. – Proactive Technologies, Inc.
Artificial Intelligence (AI) is the all-consuming topic of the day. The media, as with the Internet of Things (IoT), is the vehicle with which a well-financed marketing campaign is transformed into an illusionary “trend” train that we are all shamed into boarding lest we will be left behind. Whether being left behind is a good or bad thing is yet to be determined.
Potential employees have already been showered with generative AI employment scams, does it really make sense to turnover the recruiting, selection, training and managing responsibilities over to AI as well? The rush to IoT has left the backdoor open to any form of lone wolf or criminal organization to exploit as we are experiencing every day. Without repairing the holes in the existing interconnectivity, does it make sense to add more known risks to it?
Where there is money, there is the “newest trend” to consider. Often not actually a trend, they are more like a well-funded marketing scheme as we have come to know by hedge funds that have amassed trillions and need things to invest in to expand their presence and dominance. AI represents the culminative test of the employer’s ability to read to tea leaves correctly and the most significant challenge to employee’s gainful employment yet.
Companies collectively spent $101.6 billion last year on related technical instruction, much of it informal, unstructured and undocumented on-the-job training. Structuring what is already in place to make it deliberate, efficient and documented is a tremendous start and employers do not need AI for that. But it does take incorporating a coherent worker training strategy into the firm’s business model and treating employees as “investments.”
Prior to AI, the main technological platforms for evaluating candidates were based on a key-word search technique invented for the intelligence communities to read mountains of written material for intelligence on pending activities, threats and developments. It searched for key words and phrases associated with known perils, and the technique was applied to reading resumes. While performing this human resource management task was viewed as drudgery, key-word screening platforms continues to have drawbacks that were never really remedied. Candidates that created resumes without knowing what the keywords or phrases were found their resumes tossed aside. Conceivably, a lesser skilled and experienced candidate who new the keywords could be selected over a highly skilled and experienced candidate who didn’t. Qualified candidates were left behind and employers continued to say “they just cannot find good help.”
AI, whether packaged by someone else or programmed by unknown experience of usage, learns from humans. Humans have a lot of experience at selecting or doing the wrong things until the right one comes along… and then they might talk themselves out of the right thing since there is pressure that makes it socially riskier to be the follower than near the front of the herd with the “innovators and early adopters” where the substantial risk or early reward lies. In any event new and potential workers, already fearful of losing their jobs to AI, now have to consider that AI might be the one hiring them or making the decision to terminate them.
Companies collectively spend $101.6 billion related technical instruction, much of it informal, unstructured and undocumented on-the-job training. Structuring what is already in place to make it deliberate, efficient and documented is a tremendous start and you do not need AI for that. But it does take incorporating a coherent worker training strategy into the firm’s business model and treating employees as “investments.”
Considering the millions of potential workers exploring career paths upon graduation, what should they be told? Pick any degree program, the chance of a job in your career field choice still being around, or you being selected for it through AI, may not worth the effort, expense and distress. Too many students who spend 4 to 8 years preparing for a field of choice or a field they were told would be hiring, put in the effort and incur the cost but are kept from reaching their goal. After a massive demoralization, they usually have depleted their funds, over-obligated themselves with loans, and more importantly, are depleted of trust in whatever the “trend reporters” say. Before you say, “but these are just insignificant blue-collar jobs,” know that AI is already coming for white-collar jobs in finance, law, journalism, medicine and more.
As business leaders and homeowners came to find out, the benefits of the Internet-of-Things (IOT) trend to the end-user were significantly offset by the risks that were not discussed when the media and self-professed tech gurus hyped the wonderful new world IOT would usher in. They found out that the toaster that would text you when your toast is ready or the refrigerator that ordered groceries for you was an easy path for hackers into your privacy and other “Things” connected. That car that collects and sends all of the driver’s driving data to insurance companies, with which “risky driving habits” of not just the driver but drivers in the community as well, were used to raise insurance premiums even though no accidents or traffic tickets were recorded for the individual. Machinery that was connected to outside service providers and data storage facilities were easy pathways for hackers to inflict whatever harm they concocted.
Now we have AI. And as usual, there is a swirl of hype surrounding it. Fortunately, something was learned from the IoT experience. More people are asking important questions regarding security; both personal and digital. They are concerned that AI can be used to replicate humans in devious schemes to extort, distract, distort, lie, and destroy lives and property. Employers should be concerned about how AI could make it easier for their firm to be a target of criminals or high-tech vandals. Already stories have cropped up of AI replicating the voice of key executives of companies to have their accounting department generate payments for services not rendered or transfer of funds to offshore accounts.
So, is the solution to turn more business responsibilities over now while the herd may be stampeding toward a cliff, just to be seen by competitors and shareholders as the leaders in innovation, or to thoughtfully and deliberately consider all aspects of AI adoption and decide based on what makes business and social sense?
One threat that AI poses has gone undiscussed. Most of the AI tools will likely to be “Software as a Service” based (SaaS). What happens to all the data the AI software gathers about the company, prospective employees and employees? What happens to that data if the subscription is cancelled or the SaaS provider fails or is bought? Lawsuits have already been filed by newspapers and journalists that claim their copyrighted content was scooped up by AI to train the system and used in generating content without the cost of researching the stories, and how it will be used is a mystery to the copyright holder.
It seems small, medium and large-size businesses are exercising caution with regard to adopting AI but are attracted to the lure. Tech Radar reported, “The adoption of artificial intelligence among small and medium-sized businesses in the UK seems to have hit a crossroads, as while enthusiasm for AI tools is high, understanding and strategic planning lag behind, new research has claimed. A report from NetApp found only half (51%) of IT decision-makers surveyed understand how AI can benefit their operations, and only one in five (20%) have a strong understanding of how to harness artificial intelligence. SMBs [small and medium-size businesses) want AI, but they don’t know why. Around two in three (67%) ITDMs see AI as strategically important; however, concerns around implementation and delivery are growing, with two in five (42%) stating that their current AI adoption is not likely to deliver a return on investment. Worryingly, 15% of the SMB participants revealed that they had only adopted AI because they saw it as “jumping on a trend.” Moreover, it’s clear that uncertainty around how businesses can reap the benefits of AI is holding them back from investing, with only one in three ITDMS currently indicating that they’ve adopted AI tools.”
CNN’s Jennifer Korn reported in an article entitled “How companies are embracing generative AI for employees…or not, “Many prominent companies have entirely blocked internal ChatGPT use, including JPMorgan Chase, Northrup Grumman, Apple, Verizon, Spotify and Accenture, according to AI content detector Originality.AI, with several citing privacy and security concerns. Business leaders have also expressed worries about employees dropping proprietary information into ChatGPT and having that sensitive information potentially emerge as an output by the tool elsewhere.”
In an ABC News interview, journalist Hilke Schellmann discusses the impact of artificial intelligence (AI) on hiring, monitoring, promotion and firing in her book “The Algorithm.” Among other things, she expressed her concern over transparency as to why someone is selected or rejected, saying “…these are high stakes decisions, like, it matters who gets a job and why we get a job.” Continuing, “Why would somebody reject it? Why was somebody put in the next round? And often the even the developers of the tools do not know that because these are unsupervised AI models. So I find that very problematic. We have to have explainability, transparency.”
Even when gurus and experts promote the many speculative uses of AI in HR, a CEO has to scratch their head and wonder if this is a solution in search for a problem. Many of the claimed, and untested, uses seem to stretch the boundaries of common sense. In an article in IndustryWeek, Leo Goncalves reported that “the biggest payoff may be in professional development for current employees.” He cited “Five Ways AI Is Changing the HR Game,” and here they are:
“1. Minimize drudgery. AI has the power to liberate employees from the repetitive tasks and drudgery of rote work, enabling them to focus on more meaningful and strategic endeavors.” That is not why employees are hired; why not just say the goal is to replace employees?
“2. Building AI tools to reduce bias in hiring and promotion. Human decision-making is naturally susceptible to unconscious biases.” Where does AI get its intelligence? From the people with the bias that seems worth getting rid of. Similar to employees being flown by employers moving operations to a low-wage market and having to train the locals to accelerate the transfer of their jobs (the training effort the same employer probably did not extend to their domestic employees before deciding to move). The sum of relevant knowledge, expertise, attitude and biases will be vacuumed up by AI to form its knowledge base.
“3. Providing personalized professional-development insights that might otherwise fall through the cracks. Through the ability to process large amounts of unstructured data, AI tools can identify employees’ skills, as well as areas where they may need improvement or training.” Think this one through. Even if AI could process mountains of consequential and inconsequential data, interpreting it to be prescriptive on the skill gaps of hundreds, if not thousands, of employees (coming and going and moving laterally within the company) seems to be a fantasy. Employers have kept very little in the way of employee skill development records to set a baseline. And even if AI could do this, employers have shown they are increasingly disinterested in providing deliberate training to workers since technology appeared on the scene.
“4. Closing the skills gap. By identifying skill deficiencies near real-time at the individual level, companies can design training programs to meet specific needs that may change over time.” Same answer as 3.
“5. Upending inefficient learning pathways. Rather than imposing generic training modules on all employees in a certain role, as is common in corporate America, companies can curate content based on individual skill levels, learning styles and career goals.” “Inefficient learning pathways?” Try non-existent for many. Answer to 3 still applies.
On the bright side, there are some platforms that are rolling out (hopefully not too late) security measures applicable to AI generated content, targeting “deep fakes.” In early 2024, Meta announced that it is requiring – starting in May 2024 – a digital watermark on any AI generated image appearing on Meta platforms; Instagram, Facebook, and Threads. It later updated its AI-generated content policy and will add a “Made with AI” label. While this a step in the right direction, there is still a world of opportunities for others to corrupt the usefulness AI.
Mankind has a history of embracing new technology without thinking about the repercussion if it fails, fades or provides risky connections to other applications. While some technological advances have advanced industry, some that have been established lead to an onslaught of fraud, theft, deep fakes, manufactured “news,” phishing, malware, blackmail, extortion, theft of intellectual property and proprietary information, misinformation, disinformation and vandalism. Technological advancements have made it almost impossible for businesses and non-profits to Telemarket, since we often do not answer our phone or emails due to the threat they might offer. We have not figured how to curb those threats and there seems to be very little will by leaders to fight robocalls and threats coming from interconnectivity. Should we be so eager to add to it?
Maybe it is time for a timeout to plug the holes in what we have and not shy away from the simple solutions that have been around for centuries and have worked when applied. Employers don’t need more technology for some things; they might simply need more of an internal inventory, honest reassessment and commitment. Issues with what they have and/or have neglected to maximize may be easily remedied by looking for simple and available solutions that may fit the need and to build the smart, efficient and cost-effective path forward.
Check out Proactive Technologies’ structured on-the-job training system approach to see how it might work at your firm, your family of facilities or your region. Contact a Proactive Technologies representative today to schedule a GoToMeeting videoconference briefing to your computer. This can be followed up with an onsite presentation for you and your colleagues. A 13-minute promo briefing is available at the Proactive Technologies website and provides an overview to get you started and to help you explain it to your staff. As always, onsite presentations are available as well.
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