Humanizing AI: The Evolution of Anthropomorphism in Technology

KEY TAKEAWAYS

Humanizing AI holds promising prospects, particularly in revolutionizing our interactions with virtual agents. We can see scenarios where AI, endowed with human-like traits, can alleviate burdens and stress in sectors such as healthcare and education,

In artificial intelligence (AI), a fascinating evolution is underway — the infusion of human-like qualities into machines.

We are seeing the rise of anthropomorphism (attributing human characteristics or behaviors to an object) in AI, which brings with it a host of applications, benefits — and pitfalls.

We are stepping into the world of machines that come with a human touch.

AI with a Personal Touch

Imagine waking up to your AI assistant not just reminding you about your morning routine but doing so with a human touch — from the warmth of a human voice to dynamic dialogue as you talk about coffee, your work schedule, and even thoughts and feelings.

If nothing starts your day off better than a good argument, AI may be able to assist.

This is the new frontier of AI, where machines seamlessly adopt human characteristics.

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Project Debater: A Showcase of Humanizing AI

Project Debater from IBM serves as a prime example of how AI is being humanized. This AI system engages in debates on various topics, employing principles like data-driven speech writing, listening comprehension, and modeling human dilemmas.

It can tap into data sources, process natural language, and construct persuasive arguments, blurring the lines between human and machine intellect.

IBM says:

“It is the first AI system that can debate humans on complex topics. Project Debater digests massive texts, constructs a well-structured speech on a given topic, delivers it with clarity and purpose, and rebuts its opponent.

“Eventually, Project Debater will help people reason by providing compelling, evidence-based arguments and limiting the influence of emotion, bias, or ambiguity.”

In a world where emotion often guides matters of great importance, this will be a fascinating, albeit ethically tricky, world for AI to step into.

The Upside: Enhancing Productivity and Efficiency

Humanizing AI holds promising prospects, particularly in revolutionizing our interactions with virtual agents. We can see scenarios where AI, endowed with human-like traits, can alleviate burdens and stress in sectors such as healthcare and education — perhaps acting as a compassionate intermediary between patients and overworked healthcare professionals.

Education will likely be a key beneficiary as the tech becomes more mainstream, offering tailored tutoring methods to students with diverse learning abilities.

Risks and Challenges of Anthropomorphism

However, this rapid march towards human-like AI is not without its risks. Dependency issues, societal impacts, and mental health concerns may begin to surface as AI starts to replace real-life relationships.

Additionally, the security of personal data becomes a pressing concern, with advanced digital assistants — even services that nowadays seem pretty straightforward, like Alexa and Siri — holding increasingly sensitive information.

The Bottom Line

In the relentless pursuit of humanizing AI, a question emerges: how much is too much?

There needs to be a balanced approach, where increased productivity and resources (for instance, one-to-one tutors for education or more support as a patient moves through a health pathway) considered against the consequences to society and where potential safeguards may be needed.

However, as AI continues to impress with its instant-like ability to parse information and deliver analysis with judgment and nuance, the next stage to impress us will likely be its very human-like ways of interacting with us.

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Kaushik Pal
Technology writer

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…