How to map human and machine roles

Once you’ve figured out the problem you want to solve and that AI is the right way to go, the next step is to figure out how to apply AI. It’s important to understand whether AI should replace what a human does (which can reduce time spent on monotonous tasks and free people up) or whether AI should enhance what a person does by making it easier to do a task

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If you use Alexa, you might want to keep your pants on

As anyone knows who uses an AI voice assistant, such Alexa, Siri, Cortana or OK Google, the wake word isn’t the only thing that triggers a response. In the case of Amazon’s Echo, the phrase “my pants on” has a high chance of waking the device, risking accidentally recording the conversation and sharing it with Amazon.

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How to use an AI ethics checklist

Many organizations have developed AI ethics principles which are meant to help guide developers of AI systems. But abstract principles can be difficult to operationalize so, in response, some organizations have moved to using AI ethics checklists.

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Would you believe AI can now tell a “liar’s walk”?

New research claims to have developed AI that’s capable of detecting deception by looking at gait and gesture. This is potentially a goldmine for the AI surveillance community. But we can also see the danger. Specifically, how the seeds of bad AI can happen very early on in the development.

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According to AI, the world, and almost everything in it, are “his”

If you’re a native English speaker, you may not have consciously realized that masculine and feminine pronouns are not grammatically the same as each other. This matters because AI – specifically large, open, shared AI language models – have an important, inherent gender bias simply because of a quirk in the English language. In a

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Three ways Siri is getting better

Three interesting ideas in Apple’s research on Siri, and voice assistants in general. They are all incremental steps on the path to the holy grail of voice – an assistant that understands the user’s intent.

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So what happened with the AI behind Apple Card?

Apple and Goldman Sachs have been tweet stormed this week. Now Goldman is under investigation by the NYDFS and Apple’s brand is tarnished. None of this needed to happen. Here’s our initial conclusions and questions all leaders should ask of their AI product teams and data scientists.

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Apple Card, Goldman Sachs and sexist artificial intelligence

Apple may have inadvertently exposed sexism in the credit card business. Even the best companies in the world with the best experience with AI will stumble as Apple and Goldman Sachs are now. The question for all is: how will you create an AI governance program to manage your machine employees?

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Google set out to design more energy efficient AI but may have found something even better

Neuroscience and artificial intelligence have multiple intersection points. There are many examples of discoveries in neuroscience and psychology which provide inspiration for AI researchers, as well as the other way around. It’s a mutually reinforcing cycle as AI researchers adapt biological structures to machine architectures while neuroscientists and psychologists learn to apply various AI techniques

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If you want your teen off Snapchat, get them to watch this video

A dark humor interactive video designed to capture (literally) your attention and showcase how popular social media apps can use facial emotion recognition technology to make decisions about your life, promote inequalities, and even destabilize democracy made its debut this week. It’s particular targeted at teens and young people who use Snapchat and Instagram.

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Photo by Samuel Zeller on Unsplash

Artificial intelligence surveillance is basically everywhere

A fascinating new report details just how expansive the use of artificial intelligence surveillance is around the world. In a report released on 17 September, the Carnegie Endowment for International Peace outlines the global expansion of AI surveillance, the vast majority of it being rolled out since 2017. According to the report, “startling developments keep

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Six books Silicon Valley leaders should read before it’s too late

It feels like the start of a tech backlash. Or at least, a mid-course correction. A backlash against design that manipulates our predictable cognitive weaknesses, disrupts our attention spans and creates new forms of psychological suffering. A backlash against the constant gaming of our mental models of technology. A backlash against predictive algorithms that infer

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OpenAI’s hide and seek is more than just a game

OpenAI – the AI research group, originally founded by Elon Musk and Sam Altman and now heavily backed by Microsoft – has released some truly groundbreaking AI using reinforcement learning techniques in a multi-agent game of hide and seek. Games showcase important theoretical advances in AI, but putting too much weight on how an AI

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ethical ai

How to make ethical AI without stymying technologists

Many companies implementing AI have done so with rapid adoption of sophisticated technologies. This has lead to technologists – data scientists, AI researchers and engineers – being far ahead of the rest of the business. Leaders are having to answer the question “is your AI ethical?”

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AI that enables more sophisticated robotics and transport will not only affect jobs but also our broader social systems; changing cities and affecting the entire manufacturing, logistics and transport infrastructure.

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Design is being revolutionized. AI is enabling not only more efficient designs but truly novel constructions.

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Emotional AI measures, understands, simulates and reacts to human emotions and provides for more natural relationships between humans and machines.

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If machines can reliably interact with humans in natural language, the way we interact with technology fundamentally changes.

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AI is learning to see. Image data is increasingly available to machines which means that there are entirely new ways of using computers to help humans in the real world – extending reality and giving us new eyes.

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AI can do more than analyze and make predictions. As AI becomes increasingly specialized at a task, it can be more certain of what it knows, which enables humans to use AI to seek knowledge and truth.

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AI’s most recognized application is advanced analytics across new data sources, such as unstructured text or the internet itself. AI’s speed, scale and scope has completely changed the game as to what’s possible.

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Why a workshop for AI works

A workshop remains the gathering of choice for most leaders, particularly when there’s a need to prioritize opportunities or to align on change leadership. This is especially valuable when a company needs to figure out its AI strategy.

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How to know if AI should automate or augment

It’s important to understand whether AI should replace what a human does (which can reduce time spent on monotonous tasks and free people up) or whether AI should enhance what a person does by making it easier to do a task, making task completion more powerful or add to the skills of the individual.

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AI accuracy is confusing for most people

AI is incredible technology, something that would have been the stuff of science fiction only a few years ago. The problem is science fiction has also provided people with plenty of images of an AI surveillance dystopia. It’s hard to convey exactly how these systems work if designers only talk in probabilities.

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Augmentation vs automation

Here’s a video of Helen talking about augmentation vs automation, what humans are good at vs what machines are good at and the templates we’ve developed to help you work through these topics. Click on the image below to download the template. Try it out and let us know what you think at

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If you’re going to collect data, use it like Stitch Fix

The retail industry, while collecting a ton of customer segmentation data on websites, is lagging in deploying this data to personalize a feed for a customer. This matters because the ability to magically show a customer something that they love increases loyalty. Only a quarter of specialty retailers actually deploy the data they collect to personalize the customer experience.

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Recommended reading, listening, references and credits

We read, listen, watch and discuss with many. It’s simply impossible to include every person, podcast, video, book, paper, article we’ve touched, but we would like to acknowledge some specific expertise as well as include reading follow up for those who want to go deeper.

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armchair chat

Google’s AI is getting better at dialogue, just in time for the cloud wars

In the voice wars, context will be king. But computational efficiency matters — especially for Google which wants to be able to link the online and offline worlds, can’t position for privacy like Apple’s Siri or be always on wifi like Amazon’s Alexa devices. A true consumer, mobile, cross-platform, ad-driven experience will require both approaches to be equal priority.

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pinterest 2

Why Pinterest is an AI powerhouse

In the world of AI, context and intent are very difficult for machines to learn. What Pinterest has achieved is impressive because they are unique in their ability to serve up a personalized and contextually relevant visual experience, at scale and at speed.

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AI will have a “game changing” affect on discrimination

AI will represent a fundamental challenge to anti-discrimination regimes that seek to limit discrimination. Because AI uses training data to look for correlations that are predictive of an output with no theory or intuition from a human, it will naturally seek out proxies for genuinely predictive characteristics.

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This is how people like machines to explain themselves

Core to human-centered AI is explainability. If a machine cannot explain its reasoning in a way that humans understand and on human terms, the AI isn’t working for people. Researchers from Georgia Institute of Technology, Cornell University and the University of Kentucky recently published the results of teaching a machine to generate conversational explanations of

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AI that’s too fast will discourage people

While it may be tempting to design such robots for optimal productivity, engineers and managers need to take into consideration how the robots’ performance may affect the human workers’ effort and attitudes toward the robot and even toward themselves.

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People like advice from AI

AI must work in tandem with a professional’s desire to use his or her years of experience and sit comfortably with their intuition rather than go up against it

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Aligning technical practice with human-centered AI design

Human-centered AI design is different. To fully appreciate how speed, scale and scope of AI materially alter the standard design process, we have tailored our Sprints for AI development needs, to help technical and non-technical people come together, so that they can make better AI-enabled products, faster.

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Is AI a solution looking for a problem?

The most advanced companies today understand the scale of AI’s potential impact. They are evaluating their business problems from new perspectives. They are using the inspiration of how others are solving problems with AI to find new problems. They understand that AI’s solutions allow them to address problems they couldn’t before.

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Not all AI is good enough to increase productivity

The traditional view of automation and labor is that automation increases the value of labor by increasing the productivity of a chain of tasks. Now that more machine learning-based AI has been deployed in more places, what’s really happening is more nuanced.

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AI for Human Resources

Human-centered AI design for HR executives

Human-centered AI design makes it possible to bring in deciders—HR professionals and managers—so that they can experiment and tune the system as often as required, ultimately always having control over configuring the AI to find people in ways that truly reflect the diversity of human performance but still offering the efficiencies required.

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Why Sprint AI?

Design sprints are the hands-down best way of getting started and making early and rapid progress on a messy, upfront, ambiguous design problem. We customized them to make them work even better for AI.

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how machines learn

How Machines Learn — A non-expert guide to artificial intelligence

Artificial intelligence is one of the most important technologies of our time. AI is everywhere – it is a technology that is diffusing through everything and it touches our lives every day. This is because we are increasingly governed by our digital selves and AI powers the digital world.  ​We have spent years researching AI.

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Human-centered AI

Why human-centered AI design matters

Human-centered AI design goes beyond user interface design; it takes account of the broader implications of AI, including accountability for mistakes, ethics, bias and governance. It considers an AI to be an active agent with a distinct intelligence that it’s the responsibility of humans to design.

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Sonder Scheme

Announcing Sonder Scheme

We created Sonder Scheme to help people develop AI for humans. Our goal is to help people make better AI; AI that serves people, augments our relationships and uses this powerful technology well to advance our species.

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AI is changing strategy, competition and our time.

So far there have been two major eras in the history of computing. The first was the era of the PC from mid 70s to mid 90s. This was the heyday of IBM and then of Microsoft as they started to take over the world. This was the beginning of the desktop world with computers

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