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Is Synthetic Empathy Holding your AI back? | AI CX Chatbots

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Puneet Mehta


Human conversation is nuanced. AI is efficient. Getting the right balance of human and AI in support conversations is tricky  — but critical. 

“Are you a bot?” I asked. I had a question about a car I was researching. The bot answered my question but threw in something extra, saying, “It’s a sweet ride.” I found this mildly annoying because I suddenly could not tell whether I was speaking to a human or a bot.

Is Synthetic Empathy Holding Your AI Back?

If it was a human, I might ask different questions. If it was a bot, I really only wanted facts, not synthetic empathy.  AI can deliver answers faster and better than humans in many situations. That is the AI superpower.

Trying to make AI more human by slowing down conversations and adding in empathy when a customer knows none exists is a bad idea that diminishes the experience and annoys the customer. 

Why Synthetic Empathy Annoys Customers

Synthetic empathy is when an interaction designer endows an AI with response patterns designed to mimic human empathy.

We do this as a nod to the human tendency to constantly pad conversations with empathetic touches designed to ensure that we do not hurt someone’s feelings and to show we are paying attention to them.

I hate the fakies — how about you??

By following human conversational protocols, the communication adopts a less direct path to the resolution of a problem or question. This is a grave mistake. Forcing a circuitous path to mimic humans dilutes the superpower of AI and upsets the people it is trying to delight — your customers.  

Human conversation

Human conversation is perhaps the most inefficient communication protocol on the planet. The redundancy and empathy that form the core of normal conversation is deeply ingrained in person-to-person interactions.

We are conditioned to expect communications to happen in a certain way when we attempt to solve problems. We expect that rebooking a flight will require us to get on the phone, explain our situation, and experience an agent saying, “I’m really sorry you missed your flight. I will help you rebook.”  

That said, almost all of us would prefer saying, “Hey, Siri. My flight was canceled — rebook me on the next flight,” and having it happen instantly.

We would not recall nor care about pleasantries or empathy because our problem was solved quickly and efficiently. In this case, Siri and the AI behind it respected our time. That would actually demonstrate respect for our time — and in reality — that conversation would show the most profound demonstration of empathy.

Conversely, most of us feel annoyed when we are talking to a conversational AI support agent and it says, “Hmm, give me a second to find your records,” and inserts an artificial pause. This is a classic example of “synthetic empathy” that needlessly mimics human communications. 

Synthetic empathy can mirror — but fails to deliver truth.

Synthetic empathy can very closely mirror human empathy. But the synthetic version invariably fails to deliver on the intended effect of increasing customer happiness because it feels fake.

An even greater sin is that synthetic empathy too often injects needless friction into interactions and slows down the completion of a task.

For example, a complicated set of tasks such as troubleshooting a streaming video subscription, updating the new settings, and crediting a customer back for missed time might take 15 minutes of human interactions. The task is a couple of seconds task — not 15 minutes for an AI bot.

Speed — Speed — Speed

In this case, the best and most desired form of empathy is the speed of execution. I don’t care whether an AI lets me know that a car I am researching is a nice car. I want to ask the next question, thank you very much. 

In addition, synthetic empathy not only limits the ability of the AI to meet our needs as quickly as possible — but also redirects AI product design down a rabbit hole of human mimicry.

Once we remove the constraints of maintaining a human-like conversation, then AI becomes far more powerful and useful for humans. Product designers can think in terms of speed of resolution in AI terms rather than conversational patterns in human terms. 

The Data Says Synthetic Empathy Is Not Welcome

Synthetic empathy is rampant in AI systems today due to the belief that cognitive systems should echo the way we talk to each other.

In fact, the data doesn’t support this belief. When we surveyed X number of people about their hopes and expectations for customer service, they consistently placed speed, convenience and efficiency as their top desires.

What does your customer REALLY want?

Customers want issues to be resolved quickly and preferred not to wait. And this is a key point.

A majority of these respondents said it is crucial that companies respect their time. Granted, no customer wants services, sales, or support interactions that are rude and unpleasant. But, all things being equal, programmatic synthetic empathy will not move the need for customers — no matter how close to real-life conversations the AI can achieve.

A New Context-Dependent Definition of Empathy for AI 

This begs a bigger question. Is empathy context-dependent?

That data seems to indicate the answer is “yes,” in particular as we consider machines performing cognitive tasks. For this reason, we need to update our definition of empathy to account for the strengths of AI. And we need to avoid embedding synthetic empathy into AI.

Taking this a step further, we need to rethink customer empathy and embrace a new definition of AI empathy that prizes the timely and efficient completion of any given task. 

Customers want speed and convenience.

AI can do things in a tiny fraction of the time that a human brain takes to synthesize and communicate the task. In fact, AI can easily anticipate our needs. A really empathetic AI might note that your flight was canceled, rebook you on the next flight out, and send a text with the new flight info and a note that this is the fastest way home.

There are no pleasantries or pregnant pauses to show how human the AI is. The AI demonstrates a higher level of empathy by saving us time and hassle.

All of the desired attributes that customers want from an interaction with a company are speed, efficiency, complete resolution. These are true attributes, and they describe the improvements that efficient, focused, and task-oriented AI can bring to customer interactions.

Yes, we want AI — Just let AI do actual AI work

Only an AI can note your flight was canceled, simultaneously analyze six different flight options and instantly compute which one is the best option to rebook on to get you home as quickly as possible.

A human cannot process information as quickly and is limited by their senses. So why design AI systems with human limitations rather than AI superpowers? 

With this new definition of empathy, we can start to rethink what customer-facing AI does and how it does it. We can shift from reactive and even predictive to proactive, anticipating multiple wishes and quickly delivering them all.

With the airline example — the AI will not just rebook the flight but also schedule an Uber and text your family the new arrival information.

We can ask AI to optimize for its superpower — speed and personalization.

Programming AI for speed and personalization will make AI contextually more sympathetic by removing the synthetic version.

The gift of time and convenience is the best way to show a human you really care about them. 

Image Credit: ai jobs; pexels; thank you!

Puneet Mehta

Puneet Mehta is Founder / CEO of Netomi, a YC-backed customer experience AI platform that automatically resolves customer service issues at the highest rate in the industry. He spent much of his career as a tech entrepreneur as well as on Wall Street building trading AI. He has been recognized as a member of Advertising Age’s Creativity 50 list, and Business Insider’s Silicon Alley 100 and 35 Up-And-Coming Entrepreneurs You Need To Meet.

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Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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