Why are AI assistants given human-like names?
Apple provides Siri[i]. Amazon has Alexa[ii]. Samsung features Bixby[iii]. And there are literally dozens of other examples, in use both publicly and privately.
The attribution of human characteristics to non-human entities is known as anthropomorphism. Attributing human intent to non-human entities, such as pets, robots, or other entities, is one way that people make sense of the behaviors and events that they encounter. We as humans are a social species with a brain that evolved to quickly process social information.[iv]
There are numerous examples of anthropomorphism with which we are familiar, and honestly, don’t even think twice about. In Toy Story[v], the toys can talk. In Animal Farm[vi], the animals overthrow their masters and govern themselves. In Winnie-the-Pooh[vii], Christoper Robbin interacts with Winnie, a talking bear.
Is this why AI-enabled chatbots and digital assistants are given human-like names? To make us want to talk to them? To make it easy to interact with them? To influence our thinking and behaviors?
Without over psycho-analyzing the situation (and I am far from qualified to do so), the answer to the above questions is “yes”.
The good – and not so good – of today’s AI capabilities
AI capabilities have been around for quite some time. While philosophers and mathematicians began laying the groundwork for understanding human thought long ago[viii] , the advent of computers in the 1940s provided the technology needed to power AI. The Turing Test, introduced in 1950, provided a method for measuring a machine’s ability to exhibit behavior that is human-like. The term and field of “artificial intelligence”, coined by John McCarthy in 1956, soon followed.
The past few years have seen a dramatic expansion of AI capabilities, from machine learning to natural language processing to generative AI. That expansion has resulted in impactful and valuable capabilities for humans. AI is well-suited for managing tedious and repetitive tasks. AI can be used to initiate automated actions based on the detection of pre-defined conditions. AI can facilitate continual learning across an organization based on the data captured from interactions with and use of technology. And most recently, AI is developing a growing capability to respond to more complex queries and generating responses and prompts to aid humans in decision-making.
But despite all the progress with AI, there are some things that are not so good. Miscommunication can occur due to limitations of a chatbot or an AI assistant in understanding user intent or context. A simple example is the number of ways we as humans describe a “computer”, including “PC”, “laptop”, “monitor”, or “desktop” must be explicitly defined for an AI model to recognize the equivalence. AI is not able to exhibit empathy or the human touch, resulting in frustration, because humans feel that they are not being heard or understood.[ix] AI is not able to handle complex situations or queries that require nuanced understanding; as a result, AI may provide a generic or irrelevant response.[x] The quality of responses from AI is directly dependent upon the quality of the input data being used – and many organizations lack both the quality and quantity of data required by AI to provide the level of functionality expected by humans. Lastly, but perhaps most importantly, the expanding use and adoption of AI within organizations has resulted in fear and anxiety among employees regarding job loss.
Techniques that will help humanize AI
Several techniques can help organizations better design human interactions with AI. Here are a few to consider that can help humanize AI.
- Employing design thinking techniques – Design thinking is an approach for designing solutions with the user in mind. A design thinking technique for understanding human experience is the use of prototypes, or early models of solutions, to evaluate a concept or process. Involving the people that will be interacting with AI through prototypes can identify any likes or encountered friction in the use of AI technology.
- Mapping the customer journeys that (will) interact with AI – A customer journey map is a visual representation of a customer’s processes, needs, and perceptions throughout their interactions and relationship with an organization. It helps an organization understand the steps that customers take – both seen and unseen – when they interact with a business.[xi] Using customer journey maps helps with developing the needed empathy with the customer’s experience by identify points of frustration and delight.
- Thinking in terms of the experience – What is the experience that end-users need to have when interacting with AI? Starting AI adoption from this perspective provides the overarching direction for making the experience of interacting with AI more “human”.
Start here to make AI use more human
AI adoption presents exciting opportunities for increasing productivity and improving decision-making. But with any technology adoptions, there is the risk of providing humans with suboptimal experiences with AI. Here are three suggestions for enabling good human experiences with the use of AI.
- Define AI strategy – Success with AI begins with a well-defined strategy that identifies how AI will enable achievement of business goals and objectives. But AI success is not just business success or technical success with AI models, but also whether users are happy with AI and perceive it to be a valid solution. [xii]
- Map current customer journeys – Mapping current customer journeys may expose where user interactions are problematic and may benefit from the introduction of AI.
- Start and continually monitor the experience – Happy Signals, an experience management platform for IT, states that “humans are the best sensors”. Humans are working in technological environments that are in a constant state of change and evolution. Actively seeking out and acting upon feedback from humans regarding their experiences with technology raises awareness of the user experience and fosters a more human-centric approach to technology use and adoption.
The best way to ensure that AI-enabled technologies are more human is to design them with empathy. Design thinking, customer journey mapping, and experience management will help ensure that AI stays in touch with the “human” side.
Need help with customer journey mapping? Perhaps using design thinking techniques to develop solution-rich, human centered solutions for addressing challenges with customer and employee experience? We can help – contact Tedder Consulting for more information.
[i] “Siri” is a trademark of Apple, Inc.
[ii] “Alexa” is a trademark of Amazon.com, Inc. or its affiliates.
[iii] “Bixby” is a trademark of Samsung Electronics Co., Ltd.
[iv] https://www.psychologytoday.com/us/basics/anthropomorphism , retrieved March 2024.
[v] Lasseter, John. Toy Story. Buena Vista Pictures, 1995.
[vi] Orwell, George. Animal Farm. Collins Classics, 2021.
[vii] Milne, A.A., 1882-1956. Winnie-the-Pooh. E.P. Dutton & Co., 1926.
[viii] Wikipedia. “History of artificial intelligence”. Retrieved March 2024.
[ix] https://www.contactfusion.co.uk/the-challenges-of-using-ai-chatbots-problems-and-solutions-explored , retrieved March 2024.
[x] Ibid.
[xi] https://www.qualtrics.com/experience-management/customer/customer-journey-mapping , retrieved March 2024.
[xii] Ganesan, Kavita. “The Business Case for AI: A Leader’s Guide to AI Strategies, Best Practices, & Real-World Applications”. Opinosis Analytics Publishing, 2022.
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