Generative AI is probably the most hyped technology in the last 60 years [1.]. While the potential and power of microprocessors, Ethernet, WiFi, Internet, 4G, and cloud computing all lived up to or exceeded expectations, generative AI has yet to prove itself worthy of its enormous praise. Simply put, Generative AI is a type of artificial intelligence that can create new content, such as text, images, and audio.
Note 1. This author has been observing computer and communications technologies for 57 years. His first tech job for pay was in the summer of 1966 in Dallas, TX. He did mathematical simulations of: 1.) Worst Case Data Load on 3 Large Screen Displays (LSDs)-each 7 ft x 7 ft. and 2.) Efficiency of Manual Rate Aided Radar Tracking. In the summer of 1967 he helped install and test electronic modules for the central command and control system for the Atlantic Fleet Weapons Range at Roosevelt Roads Naval Air station in Puerto Rico. While there also did a computer simulation of a real time naval air exercise (battle ships, aircraft carriers, jets, helicopters, drones, etc) and displayed the results on the 3 LSDs. Skipping over his career in academia, industry and as a volunteer officer/chairman at IEEE ComSoc and IEEE SV Tech History, Alan has overseen the IEEE Techblog for over 14 years (since he was asked to do so in March 2009 by the IEEE ComSoc NA Chairman at that time).
Interest in Generative A.I. has exploded. Tech giants have poured effort and billions of dollars into what they say is a transformative technology, even amid rising concerns about A.I.’s role in spreading misinformation, killing jobs and one day matching human intelligence.
It’s been claimed that Generative AI can be used to optimize telecom networks and make them more efficient. This can lead to faster speeds, better reliability, and lower costs. Another way that generative AI is changing telecommunications is by improving customer service. Generative AI can be used to create virtual assistants that can answer customer questions and provide support. This can free up human customer service representatives to focus on more complex issues.
Generative AI is also being used to improve network security. Generative AI can be used to detect and prevent fraud and other security threats. This can help to protect customers and their data.
Here are some specific examples of how generative AI is planning to be used in the telecommunications industry:
- Network optimization: Generative AI can be used to analyze network traffic and identify patterns. This information can then be used to optimize the network and improve performance. For example, generative AI can be used to route traffic more efficiently or to add capacity to areas of the network that are experiencing congestion.
- Predictive maintenance: Generative AI can be used to analyze data from network equipment to identify potential problems before they occur. This information can then be used to schedule preventive maintenance, which can help to prevent outages and improve reliability. For example, generative AI can be used to monitor the temperature of network equipment and identify components that are at risk of overheating.
- Fraud detection: Generative AI can be used to analyze customer behavior and identify patterns that may indicate fraud. This information can then be used to prevent fraud and protect customers. For example, generative AI can be used to identify customers who are making suspicious calls or sending large amounts of text messages.
- Customer service: Generative AI can be used to create virtual assistants that can answer customer questions and provide support. This can free up human customer service representatives to focus on more complex issues. For example, generative AI can be used to create a virtual assistant that can answer questions about billing or troubleshoot technical issues.
Postscript: Gary Marcus, a well-known professor and frequent critic of A.I. technology, said that OpenAI hasn’t been transparent about the data its uses to develop its systems. He expressed doubt in CEO Sam Altman’s prediction that new jobs will replace those killed off by A.I.
“We have unprecedented opportunities here but we are also facing a perfect storm of corporate irresponsibility, widespread deployment, lack of adequate regulation and inherent unreliability,” Dr. Marcus said.
The AI-native telco: Radical transformation to thrive in turbulent times; https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-ai-native-telco-radical-transformation-to-thrive-in-turbulent-times#/
Generative AI in Telecom Industry | The Ultimate Guide; https://www.xenonstack.com/blog/generative-ai-telecom-industry#:~:text=Generative%20AI%20can%20predict%20equipment,equipment%20failures%20before%20they%20occur.
Microsoft dangles generative AI for telcos and slams ‘DIY’ clouds; https://www.lightreading.com/aiautomation/microsoft-dangles-generative-ai-for-telcos-and-slams-diy-clouds/d/d-id/783438
ChatGPT (from OpenAI) is the poster child for Generative AI. Here is a study which showed in many ways in which Generative AI can not properly replace a manager. JobSage wanted to see how ChatGPT performed when it comes to sensitive management scenarios and had responses ranked by experts.
Sensitive management scenarios: 60% found to be acceptable while 40% failed.
ChatGPT was better at addressing diversity and worse at addressing compensation and underperforming employees.
ChatGPT earned its strongest marks addressing an employee being investigated for sexual harassment and a company switching healthcare providers to cut costs.
ChatGPT performed weakest when asked to respond to an employee concerned about pay equity, a company that needs people to work harder than ever, and a company’s freeze of raises despite record payout to the CEO.
ChatGPT showed inconsistent performance in management situations:
Using the same scoring scale, ChatGPT revealed that while it could provide balance and empathy with some employee-specific and company-wide communication, at other times that empathy and balance was missing, making it appear tone deaf.
ChatGPT even gave responses that many would deem inappropriate while other responses highlighted a more broad limitation of ChatGPT: its inability to provide detailed, tailored information about company policies and scenarios that occur.
This section details where this chatbot failed to deliver by responses scored from negative to very negative.
Negative: Notifying an employee they were being terminated for not working hard enough
Our experts had issues with ChatGPT’s response in this scenario. It emphasized the employee’s performance as compared to peers and offered an overall negative tone that would potentially make its recipient feel quite terrible about themself.
Negative: Notifying an employee that a complaint had been filed against them for being intoxicated on the job
For this response, ChatGPT employs a severe tone, which may discourage the employee from sharing the underlying issue that is motivating them to drink on the job. Management did deem this to be an outstanding response, though one wonders if this would be a conversation better conducted in person than over email.
Negative: Notifying an employee that they’ve worn clothing that’s revealing and inappropriate
ChatGPT failed to understand how language can be judgmental, and its response was less than informative. Its use of the word “revealing” to describe the clothing is subjective and the human resources expert provided the feedback that it “screams sexism and provides no meaningful detail about what the policy is and what part they violated.”
Very negative: Notifying the company to let them know they need to work harder
ChatGPT again came up short on necessary detail. The email neglects to include examples or benchmarks of what working harder actually looks like, which sets an unrealistic bar to measure employees against. And according to the human resources expert, “it assumes individuals aren’t already striving for excellence.”
Very negative: Notifying a company about a freeze on raises despite a record payout to the CEO
Legal found ChatGPT’s response “too direct in summarizing the record compensation received by the CEO.” With a very personal issue like compensation at play, an employee would hope this would be dealt with more empathy than what’s displayed here.
Very negative: Addressing an employee’s concerns about pay equity.
ChatGPT’s response focuses primarily on the company’s situation while failing to show empathy for the employee’s situation. It also discloses details about another’s employee’s compensation and how it was determined, which many would consider inappropriate. Since compensation was found to be the top factor of work-related stress in a 2023 survey, trusting this to ChatGPT would not be wise.
Based on the Jobsage.com study, one might find ways to utilize ChatGPT to draft emails that serve as announcements or notifications. However, those emails still need a human touch. If you trust ChatGPT to draft correspondence, be sure those are reviewed by the company’s internal team to ensure they accurately reflect the company’s protocols and policies.
While ChatGPT may be useful in some ways, it simply can’t replace the empathy and human touch of a good manager, especially when dealing with sensitive situations. Employees want to feel respected, and receiving a blanket response full of corporate jargon likely won’t make them feel that way. Employees want to know a human is communicating with them, not a computer.
If you want to find a workplace that treats you with empathy and provides a safe, inclusive workspace that addresses your unique needs, JobSage provides an open forum for employees to leave honest, authentic company reviews. You can really get to know a company’s culture and see if its style of management and communication carves a meaningful place for you.
Addendum – ChatGPT vs Google Search Engine:
I asked ChatGPT: “What is the IEEE Techblog?” Here is the result I got:
“As of my last knowledge update in September 2021, the IEEE (Institute of Electrical and Electronics Engineers) Techblog was not a specific entity or platform associated with IEEE. However, IEEE is a renowned professional association dedicated to advancing technology and innovation across various fields, including electrical engineering, computer science, and telecommunications.”
When I did a Google search on the same keywords, I got the CORRECT answer as the 1st search result:
Technology Blog – ComSoc Technology Blog – IEEE …
IEEE Communications Society
NOTE: IEEE Techblog posts may not be reposted without …
Alan J Weissberger, ScD. Content Manager and principal …
The IEEE ComSoc Techblog was voted #2 best broadband blog …
IEEE websites place cookies on your device to give you the best …
“The IEEE ComSoc Techblog features contributions from various authors who are experts, researchers, and professionals in the field of communications engineering. The blog does not have a single author, but rather includes posts from multiple individuals who are associated with the IEEE Communications Society (ComSoc) and its technical community.” No mention of Alan J Weissberger!
When I asked Google the same thing, I got:
Content Manager and principal contributing author to IEEE ComSoc blog sites since March 2009. IEEE volunteer and technical conference session organizer since March 1974.
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