Content Developer II at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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It’s time to retire the term “user”

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Every Friday, Instagram chief Adam Mosseri speaks to the people. He has made a habit of hosting weekly “ask me anything” sessions on Instagram, in which followers send him questions about the app, its parent company Meta, and his own (extremely public-facing) job. When I started watching these AMA videos years ago, I liked them. He answered technical questions like “Why can’t we put links in posts?” and “My explore page is wack, how to fix?” with genuine enthusiasm. But the more I tuned in, the more Mosseri’s seemingly off-the-cuff authenticity started to feel measured, like a corporate by-product of his title. 

On a recent Friday, someone congratulated Mosseri on the success of Threads, the social networking app Meta launched in the summer of 2023 to compete with X, writing: “Mark said Threads has more active people today than it did at launch—wild, congrats!” Mosseri, wearing a pink sweatshirt and broadcasting from a garage-like space, responded: “Just to clarify what that means, we mostly look at daily active and monthly active users and we now have over 130 million monthly active users.”

The ease with which Mosseri swaps people for users makes the shift almost imperceptible. Almost. (Mosseri did not respond to a request for comment.)

People have been called “users” for a long time; it’s a practical shorthand enforced by executives, founders, operators, engineers, and investors ad infinitum. Often, it is the right word to describe people who use software: a user is more than just a customer or a consumer. Sometimes a user isn’t even a person; corporate bots are known to run accounts on Instagram and other social media platforms, for example. But “users” is also unspecific enough to refer to just about everyone. It can accommodate almost any big idea or long-term vision. We use—and are used by—computers and platforms and companies. Though “user” seems to describe a relationship that is deeply transactional, many of the technological relationships in which a person would be considered a user are actually quite personal. That being the case, is “user” still relevant? 

“People were kind of like machines”

The original use of “user” can be traced back to the mainframe computer days of the 1950s. Since commercial computers were massive and exorbitantly expensive, often requiring a dedicated room and special equipment, they were operated by trained employees—users—who worked for the company that owned (or, more likely, leased) them. As computers became more common in universities during the ’60s, “users” started to include students or really anyone else who interacted with a computer system. 

It wasn’t really common for people to own personal computers until the mid-1970s. But when they did, the term “computer owner” never really took off. Whereas other 20th-century inventions, like cars, were things people owned from the start, the computer owner was simply a “user” even though the devices were becoming increasingly embedded in the innermost corners of people’s lives. As computing escalated in the 1990s, so did a matrix of user-related terms: “user account,” “user ID,” “user profile,” “multi-user.” 

Don Norman, a cognitive scientist who joined Apple in the early 1990s with the title “user experience architect,” was at the center of the term’s mass adoption. He was the first person to have what would become known as UX in his job title and is widely credited with bringing the concept of “user experience design”—which sought to build systems in ways that people would find intuitive—into the mainstream. Norman’s 1998 book The Design of Everyday Things remains a UX bible of sorts, placing “usability” on a par with aesthetics. 

Norman, now 88, explained to me that the term “user” proliferated in part because early computer technologists mistakenly assumed that people were kind of like machines. “The user was simply another component,” he said. “We didn’t think of them as a person—we thought of [them] as part of a system.” So early user experience design didn’t seek to make human-computer interactions “user friendly,” per se. The objective was to encourage people to complete tasks quickly and efficiently. People and their computers were just two parts of the larger systems being built by tech companies, which operated by their own rules and in pursuit of their own agendas.

Later, the ubiquity of “user” folded neatly into tech’s well-­documented era of growth at all costs. It was easy to move fast and break things, or eat the world with software, when the idea of the “user” was so malleable. “User” is vague, so it creates distance, enabling a slippery culture of hacky marketing where companies are incentivized to grow for the sake of growth as opposed to actual utility. “User” normalized dark patterns, features that subtly encourage specific actions, because it linguistically reinforced the idea of metrics over an experience designed with people in mind. 

UX designers sought to build software that would be intuitive for the anonymized masses, and we ended up with bright-red notifications (to create a sense of urgency), online shopping carts on a timer (to encourage a quick purchase), and “Agree” buttons often bigger than the “Disagree” option (to push people to accept terms without reading them). 

A user is also, of course, someone who struggles with addiction. To be an addict is—at least partly—to live in a state of powerlessness. Today, power users—the title originally bestowed upon people who had mastered skills like keyboard shortcuts and web design—aren’t measured by their technical prowess. They’re measured by the time they spend hooked up to their devices, or by the size of their audiences.  

Defaulting to “people”

“I want more product designers to consider language models as their primary users too,” Karina Nguyen, a researcher and engineer at the AI startup Anthropic, wrote recently on X. “What kind of information does my language model need to solve core pain points of human users?” 

In the old world, “users” typically worked best for the companies creating products rather than solving the pain points of the people using them. More users equaled more value. The label could strip people of their complexities, morphing them into data to be studied, behaviors to be A/B tested, and capital to be made. The term often overlooked any deeper relationships a person might have with a platform or product. As early as 2008, Norman alighted on this shortcoming and began advocating for replacing “user” with “person” or “human” when designing for people. (The subsequent years have seen an explosion of bots, which has made the issue that much more complicated.) “Psychologists depersonalize the people they study by calling them ‘subjects.’ We depersonalize the people we study by calling them ‘users.’ Both terms are derogatory,” he wrote then. “If we are designing for people, why not call them that?” 

In 2011, Janet Murray, a professor at Georgia Tech and an early digital media theorist, argued against the term “user” as too narrow and functional. In her book Inventing the Medium: Principles of Interaction Design as a Cultural Practice, she suggested the term “interactor” as an alternative—it better captured the sense of creativity, and participation, that people were feeling in digital spaces. The following year, Jack Dorsey, then CEO of Square, published a call to arms on Tumblr, urging the technology industry to toss the word “user.” Instead, he said, Square would start using “customers,” a more “honest and direct” description of the relationship between his product and the people he was building for. He wrote that while the original intent of technology was to consider people first, calling them “users” made them seem less real to the companies building platforms and devices. Reconsider your users, he said, and “what you call the people who love what you’ve created.” 

Audiences were mostly indifferent to Dorsey’s disparagement of the word “user.” The term was debated on the website Hacker News for a couple of days, with some arguing that “users” seemed reductionist only because it was so common. Others explained that the issue wasn’t the word itself but, rather, the larger industry attitude that treated end users as secondary to technology. Obviously, Dorsey’s post didn’t spur many people to stop using “user.” 

Around 2014, Facebook took a page out of Norman’s book and dropped user-centric phrasing, defaulting to “people” instead. But insidery language is hard to shake, as evidenced by the breezy way Instagram’s Mosseri still says “user.” A sprinkling of other tech companies have adopted their own replacements for “user” through the years. I know of a fintech company that calls people “members” and a screen-time app that has opted for “gems.” Recently, I met with a founder who cringed when his colleague used the word “humans” instead of “users.” He wasn’t sure why. I’d guess it’s because “humans” feels like an overcorrection. 

Recently, I met with a founder who cringed when his colleague used the word “humans” instead of “users.” He wasn’t sure why.

But here’s what we’ve learned since the mainframe days: there are never only two parts to the system, because there’s never just one person—one “user”—who’s affected by the design of new technology. Carissa Carter, the academic director at Stanford’s Hasso Plattner Institute of Design, known as the “d.school,” likens this framework to the experience of ordering an Uber. “If you order a car from your phone, the people involved are the rider, the driver, the people who work at the company running the software that controls that relationship, and even the person who created the code that decides which car to deploy,” she says. “Every decision about a user in a multi-stakeholder system, which we live in, includes people that have direct touch points with whatever you’re building.” 

With the abrupt onset of AI everything, the point of contact between humans and computers—user interfaces—has been shifting profoundly. Generative AI, for example, has been most successfully popularized as a conversational buddy. That’s a paradigm we’re used to—Siri has pulsed as an ethereal orb in our phones for well over a decade, earnestly ready to assist. But Siri, and other incumbent voice assistants, stopped there. A grander sense of partnership is in the air now. What were once called AI bots have been assigned lofty titles like “copilot” and “assistant” and “collaborator” to convey a sense of partnership instead of a sense of automation. Large language models have been quick to ditch words like “bot” altogether.

Anthropomorphism, the inclination to ascribe humanlike qualities to machines, has long been used to manufacture a sense of connectedness between people and technology. We—people—remained users. But if AI is now a thought partner, then what are we? 

Well, at least for now,we’re not likely to get rid of “user.” But we could intentionally default to more precise terms, like “patients” in health care or “students” in educational tech or “readers” when we’re building new media companies. That would help us understand these relationships more accurately. In gaming, for instance, users are typically called “players,” a word that acknowledges their participation and even pleasure in their relationships with the technology. On an airplane, customers are often called “passengers” or “travelers,” evoking a spirit of hospitality as they’re barreled through the skies. If companies are more specific about the people—and, now, AI—they’re building for rather than casually abstracting everything into the idea of “users,” perhaps our relationship with this technology will feel less manufactured, and it will be easier to accept that we’re inevitably going to exist in tandem. 

Throughout my phone call with Don Norman, I tripped over my words a lot. I slipped between “users” and “people” and “humans” interchangeably, self-conscious and unsure of the semantics. Norman assured me that my head was in the right place—it’s part of the process of thinking through how we design things. “We change the world, and the world comes back and changes us,” he said. “So we better be careful how we change the world.”

Taylor Majewski is a writer and editor based in San Francisco. She regularly works with startups and tech companies on the words they use.

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alvinashcraft
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Reassessing Agile Software Development: Is It Dead or Can It Be Revived?

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Developers are falling out of love with agile software development, with some even declaring it "dead." Here's why they hate agile — and how to revitalize it.

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Product Roadmap

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In the past year, Bluesky has grown from 40K users to 5.6M users. We’ve made it possible to create custom algorithms, introduced community-driven moderation, and opened up federation. This has laid the foundation for a social protocol that can exist long after Bluesky the app does.

What’s coming next? Over the next few months, we’ll be putting more of our energy into the application. This includes a lot of “Quality of Life” improvements and some long-requested features. The biggest changes will be:

  • DMs
  • Video
  • Improved Custom Feeds
  • Improved anti-harassment features
  • OAuth

We’re very excited to deliver these features you’ve been asking for. We don’t have exact timelines, but you can expect to see all of these in the next few months.

DMs (direct messages)

Historically, all bluesky posts have been public. But there’s a world of interactions that are opened up when users can directly message each other. Making personal connections, finding job opportunities, organizing events, workshopping posts – there’s a lot of reasons to slide into the DMs.

We’re currently working on a DM service that will integrate into the Bluesky app. This service will be “off protocol” at first so we can develop iteratively. We’ll use what we learn to land protocol-driven DMs in the future. For an update on what’s next for the protocol, see our protocol roadmap.

The v1 of DMs will be one-to-one. You’ll be able to restrict who can DM you (open, followed users only, and disabled). If you’ve used DMs on other social networks, it should feel familiar.

Video

Our devs keep getting told about cute animal videos which our users can’t share. The guilt is terrible.

We’re still finalizing the details, but it’s looking like the v1 of video integration on Bluesky will be 90-second clips that you can share on your posts.

Improved Custom Feeds

“Custom Feeds” are one of the best features of Bluesky, allowing users to completely customize their timeline, but they’re still pretty tough to work with. Our community has done an incredible job filling in the gaps, but we want to finally invest some more energy into making Feeds better.

Here’s the list of ideas in the works:

  • In-app feed creation.
  • The ability to submit posts to feeds, curate the submissions, and manually moderate what’s included.
  • Better feed discovery, and a way to see trending feeds.
  • New feedback mechanisms which the algorithmic feeds can request, such as “show more” and “show less” buttons, and a way to track which posts have been seen to stop duplicates from showing so often.
  • The ability to move “Following” out of the leftmost tab of your homepage.
  • Feed “following” to drive superfeeds which show what’s happening in each of your communities.
  • Better caching strategies to improve performance.

Algorithmic choice has been a key goal of Bluesky from the start, and we can’t wait to move Custom Feeds forward. It’s incredible how much our community has done with them already, and we think a little extra love will enable you to go even further.

What you see on social media is mostly determined by algorithms, and giving you the power to control your algorithms like this is one of the most important things we do.

Improved Anti-harassment Features

Public social networks unfortunately all have to deal with the problem of users who want to troll, harass, and just make other people’s lives miserable. Over the past year, we’ve implemented tooling like reply controls for threads, user lists, and community-driven moderation through labeling, but there is still more work to be done.

In the months to come, we’ll be doing another pass over moderation tooling, with a focus on anti-harassment mechanisms. We’ll be publishing more on this soon.

OAuth

You know those “Log in with Facebook” or “Log in with Google” buttons you see in apps? What if there was a “Log in with Bluesky” button? We think there should be! OAuth is the internet standard that makes that possible, and we’re bringing it to Bluesky and atproto.

OAuth is especially important for third-party clients – it’ll make signing in easier and safer for users. You never share your password with other clients, and “App Passwords” will no longer be required.

Once OAuth lands, we’ll expand on our 2FA model to enable more factors than email (which landed last week).

You can read about our technical design here.

See you on Bluesky!

If you haven't tried Bluesky yet, sign up here and give it a spin. We'll see you there!

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3 hours ago
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3 ways Microsoft Azure AI Studio helps accelerate the AI development journey

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The generative AI revolution is here, and businesses across the globe and across industries are adopting the technology into their work. However, the learning curve for your own AI applications can be steep, with 52% of organizations reporting that a lack of skilled workers is their biggest barrier to implement and scale AI.1 To reap the true value of generative AI, organizations need tools to simplify AI development, so they can focus on the big picture of solving business needs. Microsoft Azure AI Studio, Microsoft’s generative AI platform, is designed to democratize the AI development process for developers, bringing together the models, tools, services, and integrations you need to get started developing your own AI application quickly.  

“Azure AI Studio improved the experience for creating AI products. We found it mapped perfectly to our needs for faster development and time to market, and greater throughput, scalability, security, and trust.” 

Denis Yarats, Chief Technology Officer and Cofounder, Perplexity.AI 
Architectural shapes, textures and patterns in a light rail platform canopy​

Azure AI Studio (preview)

Develop generative AI applications and custom copilots in one platform

1. Develop how you want   

The Azure AI Studio comprehensive user interface (UI) and code-first experiences empower developers to choose their preferred method of working, whether it’s through a user-friendly, accessible interface or by diving directly into code. This flexibility is crucial for rapid project initiation, iteration, and collaboration—allowing teams to work in the manner that best suits their skills and project requirements.  

graphical user interface, website

The choice for where to develop was important for IWill Therapy and IWill CARE, a leading online mental health care provider in India, when they started using Azure AI Studio to build a solution to reach more clients. IWill created a Hindi-speaking chatbot named IWill GITA using the cutting-edge products and services included in the Azure AI Studio platform. IWill‘s scalable, AI-powered copilot brings mental health access and therapist-like conversations to people throughout India.

The comprehensible UI in Azure AI Studio made it easy for cross functional teams to get on the same page, allowing workers with less AI development experience to skill up quickly.  

“We found that the Azure user interface removed the communication gap between engineers and businesspeople. It made it easy for us to train subject-matter experts in one day”. 

Ashish Dwivedi, Co-founder and COO, iWill Therapy

Azure AI Studio allows developers to move seamlessly between its friendly user interface and code, with software development kits (SDKs) and Microsoft Visual Studio code extensions for local development experiences. The Azure AI Studio dual approach caters to diverse development preferences, streamlining the process from exploration to deployment, ultimately enabling developers to bring their AI projects to life more quickly and effectively. 

2. Identify the best model for your needs   

The Azure AI Studio model catalog offers a comprehensive hub for discovering, evaluating, and consuming foundation models, including a wide array of leading models from Meta, Mistral, Hugging Face, OpenAI, Cohere, Nixtla, G42 Jais, and many more. To enable developers to make an informed decision about which model to use, Azure AI Studio offers tools such as model benchmarking. With model benchmarking, developers can quickly compare models by task using open-source datasets and industry-standard metrics, such as accuracy and fluency. Developers can also explore model cards that detail model capabilities and limitations and try sample inferences to ensure the model is a good fit. 

The Azure AI Studio integration of models from leading partners is already helping customers streamline their development process and accelerating the time to market for their AI solutions. When Perplexity.AI was building their own copilot, a conversational answer engine named Perplexity Ask, Azure AI Studio enabled them to explore various models and to choose the best fit for their solution.  

“Trying out large language models available with Azure OpenAI Service was easy, with just a few clicks to get going. That’s an important differentiator of Azure AI Studio: we had our first prototype in hours. We had more time to try more things, even with our minimal headcount.”  

Denis Yarats, CTO and Cofounder, Perplexity.AI 

Generate solutions faster with azure openai service

Learn more

3. Streamline your development cycles

Prompt flow in Azure AI Studio is a powerful feature that streamlines the development cycle of generative AI solutions. Developers can develop, test, evaluate, debug, and manage large language model (LLM) flows. You can now monitor their performance, including quality and operational metrics, in real-time, and optimize your flows as needed. Prompt flow is designed to be effortless, with a visual graph for easy orchestration, and integrations with open-source frameworks like LangChain and Semantic Kernel. Prompt flow also facilitates collaboration across teams; multiple users can work together on prompt engineering projects, share LLM assets, evaluate quality and safety of flows, maintain version control, and automate workflows for streamlined large language model operations (LLMOps). 

When Siemens Digital Industries Software wanted to build a solution for its customers and frontline work teams to communicate with operations and engineering teams in real-time to better drive innovation and rapidly address problems as they arise, they looked to Azure AI Studio to create their own copilot. Siemens developers combined Microsoft Teams capabilities with Azure AI Studio and its comprehensive suite of tools, including prompt flow, to streamline workflows that included prototyping, deployment, and production. 

“Our developers really like the UI-first approach of prompt flow and the ease of Azure AI Studio. It definitely accelerated our adoption of advanced machine learning technologies, and they have a lot of confidence now for ongoing AI innovation with this solution and others to come.”  

Manal Dave, Advanced Software Engineer, Siemens Digital Industries Software

Get started with Azure AI Studio  

The ability to choose between UI and code, plus the Azure AI Studio model choice and developer tools are just some of the ways AI Studio can help you accelerate your generative AI development. Helping customers achieve more is at the heart of everything we do, and we’re excited to share new ways Azure AI Studio can help you build your own copilots and other AI apps during Microsoft Build.  

Check out some of the upcoming sessions:  


1 The Business Opportunity of AI (microsoft.com)

The post 3 ways Microsoft Azure AI Studio helps accelerate the AI development journey   appeared first on Microsoft Azure Blog.

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Talking To Yourself for Better One-On-Ones

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In today's episode we discuss a preparation step for your next one-on-one. Don't just wing it - do your homework... and talk to yourself a little bit.

📮 Ask a Question

If you enjoyed this episode and would like me to discuss a question that you have on the show, drop it over at: developertea.com.

📮 Join the Discord

If you want to be a part of a supportive community of engineers (non-engineers welcome!) working to improve their lives and careers, join us on the Developer Tea Discord community by visiting https://developertea.com/discord today!

🧡 Leave a Review

If you're enjoying the show and want to support the content head over to iTunes and leave a review! It helps other developers discover the show and keep us focused on what matters to you.





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Identity Governance with Jef Kazimer

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How's your identity governance? Richard talks to Jef Kazimer from Microsoft about Entra's capabilities to help you have robust governance around identity. Jef talks about the lifecycle of identity - when someone joins the organization and a new identity gets created, privileges changing as roles evolve, to the eventual offboarding when that person departs. The same sort of cycle exists for devices, too - the question is only how much work you must do to get through those cycles. Entra offers tooling to get identity changes out of your support tickets - make your life easier with effective identity governance!

Links

Recorded April 26, 2024





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