# transparency Published articles for transparency. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## System helps humans predict when self-driving cars will make mistakes DevFeed: [System helps humans predict when self-driving cars will make mistakes]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-09-02T15:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [autonomous vehicles](), [Deep learning](), [Artificial Intelligence](), [Robotics](), [Simulation](), [Computer science]() Tags: [aeronautical-and-astronautical-engineering](), [ai](), [artificial-intelligence](), [autonomous-vehicles](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [concept-wrapper-network](), [cw-net](), [deep](), [electrical-engineering-and-computer-science-eecs](), [eoin-kenny](), [human-computer-interaction](), [julie-shah](), [laura-major](), [machine-learning](), [mit-schwarzman-college-of-computing](), [momchil-tomov](), [motional](), [research](), [robotics](), [safety](), [school-of-engineering](), [self-driving](), [self-driving-cars](), [simulation](), [transparency]() ### AI overview MIT and Motional researchers developed CW-Net, a method that translates an autonomous vehicle's deep-learning decisions into understandable concepts. Tests found that the explanations helped safety drivers and nonexpert users better predict vehicle behavior. ### Source excerpt A new method, called CW-Net, translates the reasoning process of an autonomous vehicle's AI system into understandable concepts that explain its behavior. ## Cloud provider postmortems: volume vs depth DevFeed: [Cloud provider postmortems: volume vs depth]() Original publisher: [Read original article]() Author: Sridhar Rajarao Published: 2026-08-05T00:00:00Z Content type: opinion Language: en Sources: [Sridhar Rajarao]() Topics: [Cloud](), [incident](), [SRE](), [site-reliability-engineering](), [engineering-culture]() Tags: [2017](), [2025](), [2026](), [aws](), [azure](), [cloud](), [dynamodb](), [engineering-culture](), [gcp](), [incident](), [incident-management](), [postmortems](), [s3](), [sre](), [transparency](), [writeup]() ### AI overview The article compares public postmortem practices among Google Cloud, Azure, and AWS. It argues that Google Cloud emphasizes high volume and speed, Azure emphasizes detailed transparency and customer accountability, and AWS publishes fewer writeups with greater depth and industry influence. ### Source excerpt GCP publishes 100+ postmortems a year. AWS publishes almost none. Azure has become the transparency leader. What each posture reveals about engineering culture, and what SREs should steal from all three. ## System Cards and Datasheets: A Technical Writers Guide DevFeed: [System Cards and Datasheets: A Technical Writers Guide]() Original publisher: [Read original article]() Author: Selvaraaju Murugesan Published: 2026-07-24T12:57:29Z Content type: article Language: en Sources: [Knowledge Management Tips, Best Practices and More]() Topics: [Large Language Model](), [technical-documentation](), [Frontier Model](), [data](), [Publishing](), [trust]() Tags: [ai](), [ai-models](), [data](), [documentation](), [frontier-model](), [governance](), [guide](), [large-language-model](), [publishing](), [technical](), [transparency](), [trust]() ### AI overview This article explains how system cards, model cards, and datasheets document AI model behavior, capabilities, limitations, evaluation methods, safety controls, intended use, and the data behind models. It presents these documents as transparency and governance tools for developers, researchers, regulators, and enterprise buyers. ### Source excerpt Large Language Model providers are publishing system cards to bring transparency into their ... The post System Cards and Datasheets: A Technical Writers Guide appeared first on Document360. ## 3 Questions: Neural transparency and the future of AI design DevFeed: [3 Questions: Neural transparency and the future of AI design]() Original publisher: [Read original article]() Author: Media Lab Published: 2026-07-15T20:25:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Neural Network](), [User Interfaces](), [interface](), [Language models]() Tags: [3-questions](), [ai](), [ai-companion](), [ai-empathy](), [ai-hallucinations](), [ai-personalization](), [ai-safety](), [ai-sycophancy](), [ai-toxicity](), [algorithms](), [anthony-baez](), [apps](), [artificial-intelligence](), [behavioral-prediction](), [character-ai](), [chatbot-behavior](), [computer-science-and-technology](), [data](), [ethics](), [faculty](), [human-ai-interaction](), [human-computer-interaction](), [interface](), [interview](), [language-models](), [large-language-models](), [machine-learning](), [mechanistic-interpretability](), [media-lab](), [mental-health](), [mit-faculty-interview](), [mit-media-lab](), [neural](), [neural-transparency](), [pat-pataranutaporn](), [persona-scores](), [persona-vectors](), [personalized-ai](), [research](), [safety](), [school-of-architecture-and-planning](), [sheer-karny](), [sunburst-visualization](), [technology-and-society](), [transparency](), [users]() ### AI overview An MIT Media Lab team introduces "neural transparency," an interface that visualizes internal patterns in AI models to help users anticipate how personalized chatbots may behave. The approach compares model activations associated with contrasting traits such as empathy, honesty, toxicity, hallucination, and sycophancy, then maps custom system prompts onto those behavior directions. ### Source excerpt Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word. ## Community feedback: How can corporations improve support for open source maintainers? DevFeed: [Community feedback: How can corporations improve support for open source maintainers?]() Original publisher: [Read original article]() Author: Google Open Source (noreply@blogger.com) Published: 2026-06-30T18:30:00Z Content type: opinion Language: en Sources: [Google Open Source Blog]() Topics: [Maintainers](), [Open Source](), [Google](), [Pull Request]() Tags: [community](), [conference](), [funding](), [maintainers](), [open-source](), [open-source-communities](), [procurement](), [sponsorship](), [sustainability](), [transparency]() ### AI overview Google Open Source reports community feedback on how corporations can better support open source maintainers. Suggestions include predictable financial support, contribution-based payments, procurement and support services, conference travel sponsorships, respect for community norms, and consistency between documentation and practice. ### Source excerpt by Sophia Vargas, Google Open Source We know that AI is actively transforming the sustainability and socio-technical dynamics of OSS communities. Google Open Source is committed to partnering with open source communities and ecosystems to learn together how we should update our own models for engagement and support. During an open meetup for GitHub Maintainer Month, I led a session to gather community feedback on how corporations can more effectively support open source maintainers. Paying maintainers takes creativity Many maintainers would appreciate consistent financial support. However, facilitating payments to individuals without established contractual relationships remains a complex challenge, particularly across diverse international jurisdictions. Fiscal hosts and programs such as Open Collective, GitHub Sponsors, and the LFX Mentorship Program can simplify components of this process, but they do not resolve the underlying issues of funding sustainability and predictability. While initiatives like the Open Source Endowment are working toward long-term funding sustainability, individual maintainers also had a few ideas: Pay per meaningful contribution vs gameable metrics: Avoid payment models based on easily manipulated units like pull request counts or review volume. A proposed alternative is 'pay per report,' encouraging maintainers to document their achievements and upcoming roadmaps. Commitment-based purchasing: Corporate policies might make procurement simpler (or more complex) than sponsorships, so maintainers could benefit from offering structured support services alongside traditional sponsorship opportunities. Fund conference attendance: In-person networking can be a boon for solo maintainers but it's often cost-prohibitive. For some corporations, travel sponsorship may be a simpler alternative to direct payments. Challenge for Corporations and Fiscal Hosts: How can we assist maintainers in understanding any and all prerequisites and documentation ne ## Reframing Healthcare Technology in the AI Era DevFeed: [Reframing Healthcare Technology in the AI Era]() Original publisher: [Read original article]() Author: Jon Wettersten Published: 2026-03-06T22:14:00Z Content type: opinion Language: en Sources: [8th Light](), [8th Light Insights]() Topics: [Artificial Intelligence](), [Generative AI](), [Automation](), [decision-making](), [trust](), [digital]() Tags: [ai](), [automation](), [decision-making](), [generative-ai](), [governance](), [healthcare](), [healthtech](), [human-centered-design](), [safety](), [technology](), [transparency](), [trust]() ### AI overview This article argues that healthcare organizations should approach AI adoption through human-centered design, stronger governance, transparency, and alignment with clinical standards. It emphasizes that clinicians need technology to reduce administrative burden and support patient care without compromising safety, trust, or practical and ethical readiness. ### Source excerpt At 8th Light, we help healthcare organizations design and build AI-enabled systems that put people first, combining product strategy, human-centered design, and technology leadership to create innovative solutions that work for clinicians as well as patients. Why This Matters Although AI continues to dominate healthtech headlines, many frontline clinicians are still battling clunky systems, fragmented workflows, and administrative overload. The reality? Healthcare practitioners are not asking for more technology, they're asking for more time with patients. The tension between innovation and adoption continues to shape healthcare's digital transformation. As AI tools quickly evolve and adapt to revolutionize diagnosis, documentation, and decision-making, many healthcare providers remain cautious. Their questions are not about the potential of technology, but about its practical and ethical readiness for real-world care. For instance: How do we vet these tools? Can we trust the outcomes? Will this actually improve care or just add more work? Will this solution deliver measurable ROI without compromising patient safety? These are not questions of resistance, they're questions of responsibility. As healthcare systems race to deploy generative AI, predictive analytics, and automation, clinicians and administrators are demanding stronger governance, transparency, and alignment with clinical standards. Their goal isn't to slow innovation, but to ensure technology protects both patients and the licensed physicians who care for them. Behind these questions lies a workforce already under significant strain, and technology that fails to ease that burden risks making it worse. The Urgent Need for Human-Centered Healthtech The U.S. is already experiencing workforce strain across many health professions, driven by geographic maldistribution, burnout, and demographic pressures. Federal workforce projections show ongoing gaps across multiple professions, with non-metro communities ## The article criticizes Google's moderation of malicious Chrome Web Store extensions DevFeed: [The article criticizes Google's moderation of malicious Chrome Web Store extensions]() Original publisher: [Read original article]() Author: Wladimir Palant Published: 2025-01-13T13:12:43Z Content type: opinion Language: en Sources: [Almost Secure]() Topics: [Google Chrome](), [Browser Extension](), [Google](), [trust]() Tags: [extension](), [google-chrome](), [reports](), [transparency](), [trust]() ### AI overview This opinion article argues that Google's moderation of malicious and problematic Chrome Web Store extensions is ineffective and inconsistent. It describes automated moderation as inadequate, says legitimate add-on authors also face problems, and cites the author's experience reporting harmful extensions. ### Source excerpt Let's make one thing clear first: I'm not singling out Google's handling of problematic and malicious browser extensions because it is worse than Microsoft's for example. No, Microsoft is probably even worse but I never bothered finding out. That's because Microsoft Edge doesn't matter, its market share is too small. Google Chrome on the other hand is used by around 90% of the users world-wide, and one would expect Google to take their responsibility to protect its users very seriously, right? After all, browser extensions are one selling point of Google Chrome, so certainly Google would make sure they are safe? Unfortunately, my experience reporting numerous malicious or otherwise problematic browser extensions speaks otherwise. Google appears to take the "least effort required" approach towards moderating Chrome Web Store. Their attempts to automate all things moderation do little to deter malicious actors, all while creating considerable issues for authors of legitimate add-ons. Even when reports reach Google's human moderation team, the actions taken are inconsistent, and Google generally shies away from taking decisive actions against established businesses. As a result, for a decade my recommendation for Chrome users has been to stay away from Chrome Web Store if possible. Whenever extensions are absolutely necessary, it should be known who is developing them, why, and how the development is being funded. Just installing some extension from Chrome Web Store, including those recommended by Google or "featured," is very likely to result in your browsing data being sold or worse. Google employees will certainly disagree with me. Sadly, much of it is organizational blindness. I am certain that you meant it well and that you did many innovative things to make it work. But looking at it from the outside, it's the result that matters. And for the end users the result is a huge (and rather dangerous) mess. Contents Some recent examples The reporting process Chrome Web ## Transparency, autonomy, responsiveness, and education: How the Aha! engineering team works DevFeed: [Transparency, autonomy, responsiveness, and education: How the Aha! engineering team works]() Original publisher: [Read original article]() Published: 2024-10-28T00:00:00Z Content type: opinion Language: en Sources: [Aha! Engineering Blog]() Topics: [Programming](), [Self-organizing Team](), [Agile](), [pair\_programming](), [Code](), [App]() Tags: [agile](), [approach](), [engineering](), [meetings](), [pair-programming](), [product](), [programming](), [security](), [team](), [teams](), [transparency](), [work]() ### AI overview The article explains how Aha!'s engineering team combines individual, pair, and team-based work. Engineers present their work in weekly meetings, retain ownership of code, and share knowledge across the organization. Small agile teams align with product areas and infrastructure, while rotating support responsibilities provide broader exposure. Product managers, designers, and engineers prioritize and scope work collaboratively. ### Source excerpt Organizations have many different ways to approach how teammates write code. You have individual silos, pair programming, team-based work, and black box interfaces where you have no idea how the other team is structured. We use a mix of these approa ## Critique of Gaia-X's role in Europe's cloud strategy DevFeed: [Critique of Gaia-X's role in Europe's cloud strategy]() Original publisher: [Read original article]() Published: 2024-07-25T10:50:43Z Content type: opinion Language: en Sources: [Bert Hubert's writings]() Topics: [gaia](), [Cloud](), [Data Space](), [interoperability]() Tags: [aws](), [cloud](), [europe](), [gaia](), [governance](), [initiative](), [interoperability](), [open-source](), [transparency]() ### AI overview The article argues that Gaia-X is an expensive distraction that is not building a European cloud and may be holding back progress. It distinguishes Gaia-X from an EU project or AWS competitor and discusses its stated focus on digital governance, transparency, portability, interoperability, Data Spaces, and open source software. ### Source excerpt It pains me that I have to write this, but Gaia-X is a harmful and expensive distraction, and it is not doing anything that will ever get us a "European cloud", not even indirectly. Its very existence is holding back progress. For this reason, Gaia-X should be abandoned, and we should try to learn as much as possible from its failure, so we can try something else. I provide some inspiration at the end of this post. ## Temporal is now a CVE Numbering Authority (CNA) DevFeed: [Temporal is now a CVE Numbering Authority (CNA)]() Original publisher: [Read original article]() Author: Brandon Sherman Published: 2023-07-20T04:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [Security](), [Vulnerabilities](), [Self-hosted](), [Software as a service]() Tags: [cve](), [product-news](), [security](), [self-hosting](), [transparency](), [vulnerabilities](), [vulnerability]() ### AI overview Temporal announces that it has joined the CVE Program as a CVE Numbering Authority, enabling clearer communication of security issues affecting its software. The article also describes CVE-2023-3485, a Temporal Server vulnerability involving namespace protection checks, and provides mitigation guidance. ### Source excerpt Temporal has been added to the CVE Program as a CVE Numbering Authority (CNA). This is a great milestone for our team and reflects our commitment to security and transparency ## Adopting the DACI Framework for Software Decision-Making DevFeed: [Adopting the DACI Framework for Software Decision-Making]() Original publisher: [Read original article]() Author: Mike Published: 2023-05-23T20:40:14Z Content type: tutorial Language: en Sources: [Dev Details]() Topics: [decision-making](), [Architecture & Design](), [Software Engineering](), [Development]() Tags: [architecture](), [collaboration](), [decision-making](), [efficiency](), [templates](), [transparency]() ### AI overview This article presents an accepted Any Decision Record for adopting the DACI framework in a software team. It explains the roles of Driver, Approvers, Contributors, and Informed, and compares DACI with RACI and RAPID. ### Source excerpt An ADR for Streamline Decision Making ## Bloco's Annual Transparency Report - 8th Year Edition DevFeed: [Bloco's Annual Transparency Report - 8th Year Edition]() Original publisher: [Read original article]() Author: Cláudia Published: 2023-04-12T15:09:00Z Content type: article Language: en Sources: [Blog - Bloco]() Topics: [Development](), [Mobile](), [Android](), [Open Source](), [App]() Tags: [about](), [android-development](), [app](), [business](), [clients](), [life](), [mobile](), [open-source](), [report](), [transparency]() ### AI overview Bloco's eighth annual transparency report covers the period from April 2022 through March 2023. It reviews client projects, internal projects, revenue and expenses, and the development and performance of its Cabinet Android app. ### Source excerpt Another year went by, one marked by many challenges and great satisfactions. This is our annual transparency report from the 1st of April'22 to the 31st of March'23. We believe companies should be as transparent as possible and this is another step in that direction. ## Dutch Electrical Power Numbers part 2 DevFeed: [Dutch Electrical Power Numbers part 2]() Original publisher: [Read original article]() Published: 2022-04-14T19:44:21Z Content type: opinion Language: en Sources: [Bert Hubert's writings]() Topics: [data](), [Network]() Tags: [data](), [energy](), [network](), [solar](), [statement](), [transmission](), [transparency](), [tso]() ### AI overview The article examines inconsistencies and gaps in Dutch electrical power-generation data reported by TenneT to the ENTSO-E transparency platform. It discusses potentially incomplete or unclear figures for solar, onshore wind, fossil gas, and the "Other" category, while noting TenneT's explanation that unidentified or unavailable generation may be grouped or omitted. ### Source excerpt In an earlier post I presented a naive model for estimating Dutch electrical solar power generation numbers. It turns out that the Dutch electrical power generation numbers are an even bigger mess than I appreciated. It appears that "everyone knows" that the numbers are confusing, incomplete and perhaps even wrong. But somehow this state of confusion isn't written down anywhere. So I'll give it a shot. A round of thanks to a small number of anonymous industry insiders that provided invaluable help! ## Code ownership conflicts as a signal for structural mismatch DevFeed: [Code ownership conflicts as a signal for structural mismatch]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2022-02-19T12:54:00Z Content type: opinion Language: en Sources: [Tobias Mende]() Topics: [Architecture & Design](), [software-architecture](), [Code](), [Software]() Tags: [architecture](), [code](), [components](), [conway-s-law](), [practices-software-development-organizational-design-software-craft](), [software-architecture](), [teams](), [transparency]() ### AI overview This opinion article argues that team-level code ownership can reveal structural mismatches between team organization and software architecture. It explains how unclear ownership, especially in larger systems, can obscure subsystem boundaries and hidden knowledge gaps. Drawing on Conway's law and the Inverse Conway Manoeuvre, it presents aligned team and architectural boundaries as a way to reinforce system structure and surface ownership issues. ### Source excerpt Code ownership conflicts as a signal for structural mismatch In my last article, I explained why I believe that individual code ownership is bad and why weak code ownership on a cross-team level can be highly beneficial. ## Temporal Transparency Update #2 DevFeed: [Temporal Transparency Update #2]() Original publisher: [Read original article]() Author: Ryland Goldstein Published: 2020-07-18T04:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [Code](), [GitHub](), [GitHub Issues]() Tags: [github](), [github-issues](), [product-news](), [progress](), [release](), [transparency](), [update]() ### AI overview Temporal's second V1 status update says the July 31, 2020 code-completion date remains unchanged. The team added tasks from open issues in public GitHub repositories, prioritized the remaining work, and expected many in-progress items to be completed that week. ### Source excerpt Hope everyone is having a great Friday. I'm happy to share our second V1 status update as part of our continued effort to be more transparent. ## Temporal Transparency Update DevFeed: [Temporal Transparency Update]() Original publisher: [Read original article]() Author: Ryland Goldstein Published: 2020-07-10T04:00:00Z Content type: news Language: en Sources: [Temporal Blog]() Topics: [reliability](), [GitHub Actions](), [interface](), [API]() Tags: [api](), [ci-cd](), [product-news](), [reliability](), [transparency](), [update]() ### AI overview Temporal provides a transparency update on its V1 release timeline. The team expected to reach code completion by July 31, 2020, then begin stabilization, while withholding a firm stable-release date until critical bugs are resolved. ### Source excerpt We believe that life is full of surprises and sometimes you can't prevent delays, but you can always have open and direct communication channels. Read our update here. ## Inside ReactOS Deutschland e.V. - Annual Report 2018 DevFeed: [Inside ReactOS Deutschland e.V. - Annual Report 2018]() Original publisher: [Read original article]() Published: 2019-06-23T00:00:00Z Content type: article Language: en Sources: [Front Page on ReactOS Website]() Topics: [ReactOS](), [Development](), [Operating system](), [USB](), [Google]() Tags: [2017](), [free](), [google-summer-of-code](), [open-source](), [organization](), [os](), [project](), [react](), [reactos](), [report](), [transparency](), [usb](), [win32](), [winapi]() ### AI overview ReactOS Deutschland e.V. published its 2018 annual report on the main ReactOS website. The report covers the association's activities, outlook, finances, support for the ReactOS Project, the ReactOS Hackfest, Google Summer of Code participation, events, releases, donations, scholarships, and USB stack contract work. ### Source excerpt The Annual Report 2018 of ReactOS Deutschland e.V., the non-profit organization supporting the ReactOS Project, has just been finished. In the past, these reports have exclusively been published on the ReactOS Deutschland e.V. subsite, but only got little attention there. Hence, the latest report is now released on the main ReactOS website. In our quest for transparency, we hope that the report offers an insight into the foundation's activities in 2018 and the plans for 2019. ## Why Data Quality Matters More Than Mathematical Complexity in Optimization Models DevFeed: [Why Data Quality Matters More Than Mathematical Complexity in Optimization Models]() Original publisher: [Read original article]() Published: 2019-06-08T08:00:06Z Content type: opinion Language: en Sources: [Jeremy Kun]() Topics: [data](), [Optimization](), [datacenter](), [Google](), [math](), [Code]() Tags: [data](), [datacenter](), [debugging](), [google](), [operations-research](), [optimization](), [transparency]() ### AI overview The article argues that obtaining reliable, maintained data is often harder and more consequential than solving the mathematical optimization problem itself. Incomplete or poor-quality data can create technical debt, edge cases, debugging work, and systems that are difficult to explain or audit. ### Source excerpt At Google, our organization designs, owns, and maintains a number of optimization models that automate the planning of Google's datacenter growth and health. As is pretty standard in supply chain optimization and planning, these models are often integer linear programs. It's a core competency of operations research, after all. One might think, "Large optimization problems? That sounds hard!" But it's actually far from the hardest part of the job. In fact, it's one of the few exciting parts of the job. ## Trust and Integrity DevFeed: [Trust and Integrity]() Original publisher: [Read original article]() Published: 2019-03-02T01:09:26Z Content type: opinion Language: en Sources: [Jessie Frazelle]() Topics: [trust](), [integrity](), [Finance]() Tags: [finance](), [integrity](), [leadership](), [transparency](), [trust]() ### AI overview A reflection on trust and integrity in workplace leadership, prompted partly by an experience in finance. The author argues that transparency, integrity, and a track record of doing the right thing are essential for leaders to build trust, while acknowledging that legal matters may require confidentiality. ### Source excerpt I stated in my first post on my reflections of leadership in other industries that I would write a follow up post after having hung out in the world of finance for a day. This is pretty easy to do when you live in NYC. Originally for college, I was a finance major at NYU Stern School of Business before transferring out, so I have always had a bit of affinity for it. I consider myself pretty good at reading people. This, of course, was not always the case. I became better at reading people after having a few really bad experiences where I should have known better than to trust someone. I've read a bunch of books on how to tell when people are lying and my favorite I called out in my books post. This is not something I wish that I had to learn but it does protect you from people who might not have the best intentions. Most people will tell you to always assume good intentions, and this is true to an extent. However, having been through some really bad experiences where I did "assume good intentions" and should not have, I tend to be less and less willing to do that. I am saying this, not because I think people in finance are shady, they aren't, but because I believe it is important in any field. I, personally, place a lot of value on trust and integrity. I'm not really going to focus this post on what an investment bankers job is like because honestly it wasn't really anything to write home about. What I did find interesting was the lack of trust in the workplace. Trust is a huge thing for me, like I said, and I think having transparency goes hand-in-hand with that. To gain trust, I believe a leader must also have integrity and a track record of doing the right thing. I liked this response to a tweet of mine about using "trust tokens" in the case leadership needs to keep something private. They are. It gets hard with legal things like SEC filings and acquisitions but that's where an already good leadership team can use existing trust tokens. -- Silvia Botros (@dbsmashe ## What does it mean for an algorithm to be fair? DevFeed: [What does it mean for an algorithm to be fair?]() Original publisher: [Read original article]() Published: 2015-07-13T09:00:00Z Content type: opinion Language: en Sources: [Jeremy Kun]() Topics: [Algorithms](), [Algorithms, Complexity](), [Machine learning](), [Programming]() Tags: [accountability](), [algorithm](), [algorithms](), [data-mining](), [deep-learning](), [discrimination](), [disparate-impact](), [fairness](), [google](), [law](), [machine-learning](), [mathematics](), [neural-networks](), [transparency]() ### AI overview The article examines algorithmic fairness and argues that algorithms trained on historical human data can facilitate illegal discrimination and reinforce social prejudices. It uses targeted loan advertising, Google autocomplete, and predictive policing as examples, though the supplied text is incomplete. ### Source excerpt In 2014 the White House commissioned a 90-day study that culminated in a report (pdf) on the state of "big data" and related technologies. The authors give many recommendations, including this central warning. Warning: algorithms can facilitate illegal discrimination! Here's a not-so-imaginary example of the problem. A bank wants people to take loans with high interest rates, and it also serves ads for these loans. A modern idea is to use an algorithm to decide, based on the sliver of known information about a user visiting a website, which advertisement to present that gives the largest chance of the user clicking on it. ## Mixing personal and professional, Transparency DevFeed: [Mixing personal and professional, Transparency]() Original publisher: [Read original article]() Author: Map Published: 2008-06-04T09:57:16Z Content type: opinion Language: en Sources: [Craig Kerstiens]() Topics: [X (Twitter)]() Tags: [personal](), [personal-life](), [relationships](), [transparency](), [twitter]() ### AI overview The author explains why they support blending personal and professional communication, including sharing career changes and maintaining relationships through Twitter and other social tools. They argue that this transparency can deepen professional relationships while acknowledging that some people prefer stricter boundaries. ### Source excerpt Someone recently commented on by tweeting after having given my two weeks notice to my company, that it may not have been the best idea. So as a result I'd like to post my reasoning and thought why I feel it is actually a great idea. Even a month before my giving two weeks notice many knew it was likely going to happen, and I personally hope that this allowed those that may have needed to, to better plan accordingly. This also I believe allows me to be more evaluated on my actual merit in some terms. You see if I made it clear that I might be looking at another opportunity, and was not wanted I believe there may have been good reason hints would have been given that I should look harder and more. Instead in was a reasonable bit of the opposite. However the larger point of what I'd like to illustrate is that many of those that I work with I view as more than strictly co-workers. It's not uncommon to meet up with them on a Saturday for drinks or to just hang out. Meanwhile I have many friends who I do not talk to on a daily or even weekly basis, yet still like to keep them informed of what I'm up to, just as I look to follow how they are. To me twitter and other social tools are this medium. While some may prefer to keep professional and personal strictly separate entities, I have no problem with the two blurring. In fact I believe it adds to what I bring to the table in both contexts. By no means do I live and breath work, but to me my work is not only a job either. There are times after 5 or 6 o'clock that I will spend reading about business and technology, in short because they interest me. Though there are times between 8 and 5, that I will have an IM conversation un-work related, or post tweets available to the rest of the world. Hopefully some may value this transparency, though if you do not, dont add me on facebook, dont follow me on twitter. You'll still get the formal good-bye email with the rest of the group, however, I wouldn't expect you to get updates in