{"id":35322,"date":"2024-05-22T10:34:18","date_gmt":"2024-05-22T09:34:18","guid":{"rendered":"https:\/\/digileaders.com\/?p=35322"},"modified":"2024-05-23T12:04:33","modified_gmt":"2024-05-23T11:04:33","slug":"enough-with-the-chatbots-already","status":"publish","type":"post","link":"https:\/\/digileaders.com\/enough-with-the-chatbots-already\/","title":{"rendered":"Enough with the chatbots already"},"content":{"rendered":"

We\u2019ve all been there. Stuck with a \u201chelpful\u201d online chatbot when all you want to do is speak to a real person. It\u2019s the modern equivalent of the 90s Windows paperclip\u2026<\/p>\n

But while this seems to be an almost universal experience, chatbots are now popping up everywhere. From customer service and healthcare to banking and security \u2013 there\u2019s a bot for that. How did we end up with such a disconnect between business expectation and user reality?<\/p>\n

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A chatbot, for chatbot\u2019s sake<\/h3>\n

The galloping excitement around AI means organisations are falling over themselves to add a chatbot as fast as possible. The only question that gets asked is \u201chow long till it\u2019s set up?\u201d<\/p>\n

After all, most organisations are battling with how to get customers the information they need at the right time and in the right way. A chatbot feels like a magic bullet, an easy fix. An AI assistant that never sleeps and has all the information at its (virtual) fingertips \u2013 hooray! In all the rush, the focus ends up on the platform itself instead of on our users.<\/p>\n

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Chatbots and AI<\/h3>\n

Chatbots have long suffered from being set up with little thought. The old scripted versions had a bad reputation for simply regurgitating corporate FAQs. People ran the chatbot gauntlet only in the (often vain) hope that a human was on the other side.<\/p>\n

Modern chatbots don\u2019t follow a predetermined script. Instead they\u2019re based on a type of AI known as a Large Language Model (LLM). This allows them to process and predict what was previously an exclusively human to human interface: language.<\/p>\n

As such they are a type of \u201cgenerative\u201d AI: AI that can generate its own original content. Most are \u201cretrieval augmented\u201d. That simply means they retrieve their answers from a set content source.<\/p>\n

The addition of AI theoretically makes these modern bots much more powerful. But when they are poorly thought through and poorly implemented, it mostly makes them more powerfully irritating.<\/p>\n

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The impact of bad chatbots<\/h3>\n

We do not need to imagine the impact of poor chatbot implementation. Right now the media is full of delighted stories of people getting the better of bots.<\/p>\n

One bot offered\u00a0a great deal on a car<\/a>. Another\u00a0composed a haiku about how bad it was<\/a>\u00a0and we\u2019re even\u00a0starting to see court cases<\/a>. But that\u2019s just the tip of the proverbial iceberg.<\/p>\n

In the face of so many bad experiences, users are increasingly exasperated and disappointed by bots. The impact of this is corrosive. When chatting to the team about chatbots, I found a common thread to our research insights that users increasingly:<\/p>\n