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Employee assistance programs, Mental health, etc. a task that continues to seem “too human” to delegate to AI is supporting employees during emotional or mental health difficulties, especially when they find it hard to express their emotions. Sometimes, people don't express even when it is clear, or they exhibit frustration that truly hides burnout, anxiety, or even early indicators of depression. Although AI may not currently be able to kick off these conversations, I can imagine it as a discreet supporter operating in the background. For instance, AI could identify behavioral patterns such as a decrease attendance, or meeting attendance, alterations in communication styles, or numerous emails sent late at night and subtly notify HR or supervisors regarding these concerns. It might also suggest wellness resources or conversation starters tailored to the context, facilitating opportunities for meaningful human engagement. In this way, AI serves as a support system, not a substitute making certain that no one slips through the cracks, particularly when they are unable to express their emotions.

Forum question 756 In a customer service environment when an customer service representative (Rep) is answering a query.on a voice call It is easy to determine if the Rep is using an unprofessional language or is curt or rude in a specific voice interaction. However, it is very difficult to identify if the Rep was sarcastic and fooling the customer and trying to develop a situation where he or she does not have to answer the query or help the customers. Politeness, Tone of voice is difficult to identify using AI or speech analytics. Sometimes the Speaker can sound very polite or genuine but might not necessarily be helpful in a transaction. E.g In a telecom customer service if the customer says he has relocated to a different address and now the internet dongle does not work in the new location. Instead of helping the customer if the Rep keeps asking unnecessary questions like: Oh have you never done this before? do you know how is device works? have you ever worked with advanced Modems or Mesh routers before? - All under the pretext of probing questions -- some ignorant or insecure customers are ashamed to continue conversations that they are not tech savvy enough and better to get a paid network engineer on site rather than talk to tech support, just say thank you and hang up the voice calls. I think if we can train AI or Bots on how to recognise sarcasm patterns in a spoken language it will be an added advantage. In today's speech analytics, choice of words, tonality, intonations and voice modulation is used to draw heat maps and sentiment mapping. However, as technology, we have not yet empowered AI to understand a wide range of human emotions like sarcasm. AI takes every spoken or typed word on its face value and does not get the hidden meaning behind what was said. e.g. 1) if someone has written an unsatisfactory review of a product and mentioned. the words "Nothing-life-altering-about-it" might be taken as a positive review, or 2) If someone is love waiting in traffic and listening to horn music for hours might be misconstrued as positive when it is, infact, sarcastic and displays a negative sentiment 3) While commenting on a bad lecture or speech if someone says "oh that was an award winning performance" if we ask AI to analyse it, it might take the words on face value and denote it as positive. We need to train AI to understand the hidden meaning behind spoken words by feeding some books on how to understand sarcasm. Then, maybe to some level AI can start identifying negative sentiments wrapped in positive words and hidden meanings while we put things in context or perspective.

Hi, In my line of work, handling highly sensitive customer complaints/escalations which involves handling complex & emotional customers is a task that feels too human to hand over to AI How I can reimagine the role of AI in this: Analyse & Categorise: AI can analyse the initial complaint, the tone on the call or email and categories the level of emotional distress and flag the case details along with a sentiment analysis for operators to be prepared to handle the customer appropriately Providing real time support & information: AI can extract info from back end DBs on the past history of the customer, the issues reported in the past and the policies that can help the operator to handle the issue. Sentiment Analysis & Emotional Cues: AI can perform real time sentiment analysis to detect subtle changes in tone and call out the emotional changes during calls, thereby helping operators to tailor their responses. Generating summaries for documentation: All of the customer handlings are recorded and operators spend time to document the interaction & record + save evidences of their responses/resolutin to the highly sensitive customer complaints. AI can generate these responses in parallel to the transaction, thereby eliminating the entire manual documentation process Future knowledge & best practice sharing Using these documentations, better Training need analysis can be done. Best practice sharing by utilising the way other operators handled a complex customer can be used for enhancing training material. Also, AI can learn and evolve better to handle future customers with better insights over time. Vidhya R

The one thing i would like to focus upon is "Tacit knowledge". Currently, IMHO, feel that AI lacks that ability to possess that "Tacit knowledge", in several areas (in specific situations or in several industries). It is too human to hand over to AI Example: Lets take an example in substantiating the claim that i made above. As a workplace foundation coach and also an enterprise agile coach, i deal with many individuals and teams. The knowledge and experience that a coach have accrued over a period of time is difficult to be conveyed and replicated in AI in my purview. Especially when dealing with people on coaching, the emotional intelligence is a key aspect. IMHO, therefore it is not easy to train AI models on these aspects however sophisticated they be. How you might reimagine it to make AI a valuable contributor? W.r.t examples related to the activities of say coaching/consulting (say Psychologist)/healing following can be useful steps 1. Build Capability/Train on emotional intelligence for the AI systems 2. After capability is built, feed dummy problem statement (similar to the original problem where human beings were used for the activities) for coaching/consulting and check how results are coming out. 3. Compare the human based outcome vs AI generated results/outcome 4. If not satisfactory, then inspect where the gap is and adapt accordingly In General, wherever 'tacit knowledge' is needed, you may need all these 4 steps. There are many areas in which AI is difficult to be leveraged. But nevertheless, i feel these steps could be by and large common - Build the corresponding capability, test the capability built with a sample data, compare that with existing ecosystem (human driven) and if satisfactory you move to AI based; else then inspect where the gap is and adapt accordingly. Also please do take a look at Polanyi paradox that gives some additional info on 'tacit knowledge' and 'emotional intelligence' aspect "https://www.benchmarksixsigma.com/forum/topic/39795-polanyi%E2%80%99s-paradox/" Conclusion: IMHO, there are quite a few areas like 'Tacit knowledge' which are difficult to be achieved through AI. In general, any task or decision for which you are (made) accountable, you would want to manually do it and would not rely on AI. This may be due to a psychology fear (That there could be a backlash if things go awry and it stems from the fact that most of the people, do not trust technology especially when they do not have too much grip or understanding on that). Therefore, IMHO, such tasks or decisions belong to this category of too human to handover to AI. So that kind of tasks/decisions are difficult to be reimagined in AI way. Better understanding of AI can increase people's confidence (for instance, where its power lies and where can be pitfalls in its usage - if that can be understand by people). This can help in transforming such manual works to AI based