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Creating user value with AI

#artificialintelligence

Businesses are rushing to implement and develop AI solutions and products to compete in a rapidly growing market. In 2016 it was estimated that AI will be a 70 billion dollar industry by 2020 and businesses are still just scratching the surface of leveraging the full potential of the technology. However, this mission for us designers may sound too tech-driven. The AI and machine learning field still feels strongly dominated by computer scientists and developers and the voice of users often seems faint in the field. But our oath as designers is to advocate for our users and make sure to focus on their needs.


Questioning the AI: Informing Design Practices for Explainable AI User Experiences

arXiv.org Artificial Intelligence

A surge of interest in explainable AI (XAI) has led to a vast collection of algorithmic work on the topic. While many recognize the necessity to incorporate explainability features in AI systems, how to address real-world user needs for understanding AI remains an open question. By interviewing 20 UX and design practitioners working on various AI products, we seek to identify gaps between the current XAI algorithmic work and practices to create explainable AI products. To do so, we develop an algorithm-informed XAI question bank in which user needs for explainability are represented as prototypical questions users might ask about the AI, and use it as a study probe. Our work contributes insights into the design space of XAI, informs efforts to support design practices in this space, and identifies opportunities for future XAI work. We also provide an extended XAI question bank and discuss how it can be used for creating user-centered XAI.


The Three Questions about AI that Startups Need to Ask

#artificialintelligence

Billion-dollar investments in AI are booming. What does this mean for startups looking to AI for their innovative and competitive edge? The strategy seems simple: take one of humanity's perennial problems and fix it with machine learning. Google, Facebook, Netflix, and Uber did it. It can often seem like the obvious question is why not use AI?


Designing for AI-enhanced Experiences - TandemSeven - Experience design and delivery

#artificialintelligence

Barriers are continually dissolving when it comes to the capabilities of machine learning programs. As an experience strategy and design professional, I find myself asking more frequently, "Are there relevant design principles I should consider when creating these new types of digital experiences?" Many of these platforms have an opacity that can affect the overall user experience in a variety of ways. In this blog post, I'll suggest guidelines for constructing AI-enhanced experiences, and apply them to examples in the healthcare, consumer, and financial sectors. The principles I cover may not apply uniformly to all digital experiences, since other factors might predominate.


Designing for AI-enhanced Experiences

#artificialintelligence

Barriers are continually dissolving when it comes to the capabilities of machine learning programs. As an experience strategy and design professional, I find myself asking more frequently, "Are there relevant design principles I should consider when creating these new types of digital experiences?" Many of these platforms have an opacity that can affect the overall user experience in a variety of ways. In this blog post, I'll suggest guidelines for constructing AI-enhanced experiences, and apply them to examples in the healthcare, consumer, and financial sectors. The principles I cover may not apply uniformly to all digital experiences, since other factors might predominate.