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Data Science Certifications Guide 2026

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Data is an asset for every business today. With the evolution and large-scale adoption of artificial intelligence and machine learning, the global data science industry is projected to reach $470.92 billion by 2030, with a 26% CAGR from 2024 to 2030. This triggers a big-time need for data scientists. But to become one, you need knowledge and a skillset, as data analytics requires expertise in tools and techniques to make the best of it. And the data certification course can be a great start for this. Here, I will take you through the top online data science certifications for 2026. We will also discuss the scope of growth in the domain and how to select the right course.

What is a Data Science Certification?

The very first thing that you need to know is that certification & certificates are different from each other, though they sound similar, yet they hold different values and criteria for validation. A certificate is proof of completion of a program or training, whereas a certification proves the industry-level expertise and practical knowledge. 

A data science certification is a credential that proves your capability to apply data science skills, such as analysis, machine learning, and modeling, to make a better world. This requires exams or assessments by a globally recognized organization or institution.

Can you become a data scientist with a certification? 

Are you in doubt whether a certification will get you a job or not in the data science field? The answer is that if you are just looking to enhance your resume by adding extra knowledge, then only a certificate will not necessarily provide you with the desired job. You need skills and industry-level practical expertise that are often acquired by completing a certification programme. 

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Traditionally, entering a field required a bachelor’s degree and a complete knowledge of the industry. But the AI boom has built a connection between different tech domains and opened new pathways and new career opportunities. It has made career upscale & career switch way more efficient yet competitive. Therefore, certifications are helpful if you are from a technical background but need specialization in a particular field to land a job.

Data scientists need to have an understanding of statistical analysis, computing, machine learning, data analysis, visualization, and programming skills. Also, the hiring chances increase when you are familiar with the tools and libraries that data scientists use. 

Tips to choose the right data science certification courses online. 

  • Goals and Skills: First, define what you want from the course, is it skills, expert guidance, networking opportunities, or just some theoretical insights? You must make sure that your career plans align with the course you are opting for. 
  • Cost: How costly is it? Is it offering me value at this point in my career?
  • Qualifications: What are the eligibility criteria for the course? If I do not qualify currently, what more do I need to do, and is doing the course worth it at this point? 
  • Time and Mode: What is the duration of the programme? Will it be workable with my current schedule? Is the course online or offline, or do they have practicals in person during the course? 
  • Review: What do people have to say about the course? Check the online rating and feedback, discussions about the provider on public platforms such as Reddit or Quora. 
  • Job Opportunities: Check whether they offer a data science course with placement assistance or networking opportunities to get a job. Do they have a strong alumni network? 

Top Data Science Certifications Online 2026

Here is a list of globally recognized courses in the field of data science.

1. DASCA’s Data Scientist Certification

DASCA’s Data Scientist Certification
Source: Rome Business School

DASCA refers to the Data Science Council of America, and it offers courses across fields of data. As for data science, they have a Senior Data Scientist Course & a Principal Data Scientist. Both of these are great data science certifications for working professionals who already have a firm grounding in the respective field and wish to upskill. 

These certifications will offer you skills like planning, designing, and managing large-scale data systems of modeling, data mining & research. 

Demonstration of advanced skills by certified professionals across analytical operations, developing business cases, and working with teams across global organizations. 

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It is ranked and recommended by top educational and industry leaders, including Indeed, edureka, World Data Science & AI Initiative, Datamation, and more. 

Some key benefits include:

  • Global recognition and industry demand
  • Continuously evolving and research-backed knowledge for both existing and emerging data science careers
  • Cross-platform efficiency and adaptability
  • Strong network and collaboration opportunities
  • Enhanced credibility and thought leadership

2. Microsoft Certified Azure Data Scientist Associate

Microsoft Certified Azure Data Scientist Associate
Source: ProjectPro

This certification can be a great step towards excellence in data science. It is an intermediate-level course with a renewal every 12 months. You need to have certain qualifications for applying to this course, which are subject matter expertise in the application and implementation of data science and machine learning to run ML workloads on Azure, ML Flow, Azure AI Foundry, Azure AI Services, including Azure AI Search.

You can find various resources on the official website to prepare for the examination. Including all the advantages of learning from this course, you’ll also be earning a token for deploying an ML or any data science model. That model can be used as a Service by businesses, cloud consultants, and developers, too. 

3. IBM Data Science Professional Certificate

IBM Data Science Professional Certificate
Source: Cursin

This course does not demand any prior computer science or programming experience. It will offer you the job-ready skills and practical experience needed to kickstart your career in data science and machine learning. 

You will learn Python programming, SQL for database querying, data manipulation with Pandas and Numpy, data visualization using Matplotlib and Seaborn, and ML with Scikit-learn. You will actively work with data science tools like Jupyter Notebooks, RStudio, and IBM WatsonX. Use GitHub for version control and accessing data sources with APIs. Labs, coursework projects, and a capstone project will gain you valuable experience. 

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Also, this course gives unlimited access to all of its 10 courses at different price and duration packages. 

4. AWS Certified Machine Learning – Speciality

AWS Certified Machine Learning – Speciality
Source: Towards AI

The certificate credentials will badge you with the capability to architect ML/deep learning workloads, optimize model training, and implement production-ready ML systems. You will be specialized in building and deploying ML solutions in the AWS Cloud. It is an advanced-level course with a renewal period of 3 years. 

You can test your skills in data engineering, exploratory data analysis, feature engineering, model training, tuning, and deployment on services like Amazon SageMaker, Amazon S3, and AWS Lambda. Artificial intelligence practices and model interpretability will also be taught. 

5. Professional Certificate in Data Science (Harvard)

Professional Certificate in Data Science (Harvard)

This is one of the best data science certifications for beginners offered by Harvard University via edX, which will teach you the basics of data mining, visualization, probability, statistical concepts, and machine learning. You will also understand the fundamentals of R programming. It is a self-paced learning ideal for people who want to progress at their own speed. It is a 9-skills course with topics varying from linear regression to data visualization in R. 

6. Google Data Analytics Professional Certificate

Google Data Analytics Professional Certificate
Source: YouTube

This course will provide you with in-demand skills and AI training from Google experts, with learning at your own pace without a degree or prior experience. The course has a flexible schedule of 6 months at 10 hours a week. It is a beginner-level course. 

You will gain an immersive understanding of how and what junior or associate data analyst do in their everyday job. Analytical skills, including data cleaning, analysis, and visualization, and tools like spreadsheets, SQL, Python, and Tableau, will be taught. You will also learn to present the data findings on dashboards, presentations, and commonly used visualization platforms. 

Salary after Data Science Certification 

Employment in the field of data science is projected to grow 34 % from 2024 to 2034, which is faster than average for all occupations. And as per insights from Indeed, the average base salary of a data scientist in the U.S. is $129,141 per annum. And some of the highest-paying cities for the job are San Francisco, Livermore, Seattle, Palo Alto, and more. 

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Conclusion

Data science is more of an emerging domain of the tech field, but a booming industry; the average market growth is higher compared to other occupations. If you are interested in dealing with numbers that are assets to big corporations and thinking about how to become a data scientist without a degree, I have got you. You can achieve this by leveraging data science certifications. In this writing, I have mentioned several affordable data science certification courses in 2026, from beginner level to advanced level. Each of which will give you expertise about different verticals of machine learning, artificial intelligence, and analytical tools used by tech giants. 

Related: Top AI Certifications to Accelerate Your Career

FAQs

Who can apply for data science certification courses?

Students, freshers, and professionals all apply for these courses. Generally, there is no requirement for prior experience or a degree, though different courses have their own qualifications and criteria. 

Do I need to know how to code before applying for a data science certification?

Not necessarily always. Some courses, such as the IMB Data Science professional Certificate, start from the basics. And advanced courses like Microsoft Azure Certified Data Science Associate demand the knowledge of application and implementation of data science and machine learning for workloads in Azure. 

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What is the duration of courses?

It can vary from 3 to 6 months, based on your course structure and learning pace. 

How much can I earn after doing a data science certification?

It completely depends on factors like your experience and skills, region, and market demands. But certifications and projects can always offer you an edge over the competition.

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Instagram’s new Instants tool is a brazen copycat of Snapchat and BeReal, but at least it keeps things real

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Instagram has never been shy about borrowing ideas, and its latest move makes that clearer than ever. The platform just globally launched Instants, a new feature that lets you share disappearing, unedited photos with your Close Friends or mutual followers.

The standalone Instants app is now available on iOS and Android, which opens directly to the camera when you log in with your Instagram account.

Introducing Instants: the newest way to share photos in real time with your Close Friends (or mutual followers) that disappear after 24 hours and can’t be edited, so you’re sharing your most authentic moments. You can access Instants through @instagram or the new Instants app.…

— Meta Newsroom (@MetaNewsroom) May 13, 2026

How does Instants actually work?

You can also access this tool directly from the Instagram inbox. Just tap the mini photo stack in the bottom right corner of your DM inbox to open the Instants camera.

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Either way, you snap something in real time and send it instantly. No uploads from your photo gallery are allowed, and you cannot edit the image before sending. Recipients can react with emoji, reply, or fire back their own Instants.

No one can take screenshots on Instants, and photos vanish after being viewed once, and anything unopened disappears after 24 hours. In fact, anything unopened disappears after 24 hours.

If you accidentally send something, there is an undo button to take it back before anyone sees it. Your sent photos are saved in a private archive that only you can access for up to a year. You can also compile them into a recap to post to Stories later.

So which app did Instagram copy this time?

Honestly, take your pick. The disappearing photos and one-time viewing are straight out of Snapchat‘s playbook, which has offered ephemeral photo sharing since 2011. The no-edit, share-as-it-happens format is pure BeReal, an app that briefly took the world by storm by pushing users to post unfiltered photos at random times of the day.

Instants also draws comparisons to Locket, a widget-based app focused on sharing candid photos directly with close friends. But this isn’t new for Instagram because Stories was a direct lift from Snapchat, and Reels borrowed heavily from TikTok. Instants continues that tradition without much apology.

But here’s the thing – it might actually be useful

For all the eye-rolling the clone label deserves, Instants taps into something real. Instagram has spent years drifting toward influencer content, brand deals, and algorithmically pushed posts from strangers.

Instants pulls the app back toward what it was originally built for, sharing genuine moments with people you actually know. In a feed full of perfectly lit brand content, a little unfiltered reality is hard to argue with. Whether anyone actually needs it is another question, especially when BeReal never quite held on and Instagram Stories already does the job for most people.

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When it comes to academic authorship, are women at a disadvantage?

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Mary M Hausfeld of the University of Limerick explores how the process by which researchers receive credit for their work can be more complicated for women.

Scientific discoveries rarely happen alone. Modern research often involves teams spanning institutions and even countries. Yet when research is published in academic journals, credit is reduced to a list of names – a list that can shape careers.

Authorship is a key signal of expertise. It influences hiring, promotion and funding decisions. Despite this importance, the process for determining authorship is often far from transparent.

In principle, authorship should reflect intellectual contributions. In practice, decisions about who becomes an author and whose name appears in the most prized position – often first or last – are negotiated within research teams. My research with colleagues has found that women report more negative experiences around authorship decisions.

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Norms vary widely across disciplines, and unclear standards combined with power dynamics can create problems, especially for women researchers.

One of these is ghost authorship: when researchers who meaningfully contribute do not receive authorship. Another is gift authorship: when individuals who do not meaningfully contribute are included as authors.

Deciding who gets credit for a research project is complicated, even when everyone has positive intentions. These collaborations can span years, and individual roles often shift over time. Students graduate, researchers move institutions and projects evolve. As a result, authorship decisions are often shaped not just by contributions, but by a set of informal or ‘hidden’ rules that are rarely made explicit.

These hidden rules can include power dynamics between senior and junior researchers. Junior researchers, such as PhD students and postdocs, often depend on supervisors for funding and future opportunities. This can make it difficult to raise concerns about authorship.

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The standards for determining contributions may be ambiguous. While there’s recently been more discussion about the different ways someone can contribute to a project, authors may disagree about which contributions matter most. For example, how should writing the paper be weighed against collecting or analysing the data?

Fear of reputational harm could also discourage open discussion about credit. Because researchers are concerned about being labelled ‘difficult to work with’ they may avoid raising concerns about authorship, even when the stakes are high.

Gifts and ghosts

To see how these decisions play out in practice, my collaborators and I surveyed more than 3,500 researchers across 12 countries – one of the largest studies of its kind. We asked researchers about their experiences with disagreement about authorship, comfort discussing authorship in their teams and experiences with problematic authorship practices.

We found that questionable authorship practices are remarkably common. In our study, 68pc of researchers observed gift authorship, and 55pc of researchers observed ghost authorship.

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While experiences of authorship were similar across researchers in the natural sciences and social sciences, another pattern emerged. Women researchers reported experiencing more problematic authorship practices in collaborations. They encountered more disagreements over authorship decisions and felt less comfortable raising authorship concerns.

This is especially concerning given what researchers call the “leaky pipeline” in academia – where women are more likely to leave the field or are less likely to progress to senior positions over time. These patterns suggest that the hidden rules of authorship affect women and men differently.

Why it matters

These numbers aren’t just statistics. They represent missed opportunities, strained collaborations and careers quietly knocked off course. Authorship plays a central role in research careers, and even small differences in recognition can accumulate over time. When credit is uneven, opportunities become uneven. This shapes who stays in academia and whose ideas define a field. Over time, this may also push talented researchers away from academic careers or worsen existing inequalities like the leaky pipeline.

Universities rely on collaborative environments that are not only productive, but also fair. Addressing issues with authorship and its hidden rules is essential to continue moving toward better science.

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In a separate study of US PhD-granting universities, my colleagues and I found that fewer than 25pc had publicly available authorship policies. Even when policies did exist, they rarely offered guidance on how to handle concerns or resolve conflicts. Clearer institutional guidance and accessible dispute resolution procedures would provide researchers with a framework to more effectively navigate authorship.

In addition, authorship training can encourage earlier and more open conversations about authorship within research teams, particularly for junior researchers who may feel less comfortable raising these issues. Promoting more transparent documentation of individual contributions can help ensure that authorship reflects the work that was actually done, even as roles evolve over the course of a project. Training would clearly benefit early-career scholars, but would also be important for more senior academics who supervise doctoral students and help shape research norms.

When authorship is transparent and openly discussed, it can empower stronger research teams, more equitable career progression and greater trust in the scientific process. Science is a team effort, and our systems for giving credit should reflect that reality.

The Conversation

By Mary M Hausfeld

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Mary M Hausfeld is an assistant professor in management, at the University of Limerick. Her research focuses on leadership, diversity at work and research methods. Hausfeld is especially interested in the conceptual and methodological gap between what leaders do and how they are evaluated. Her work has been published in outlets including Journal of Management and others. Before joining UL, Hausfeld served as a post-doctoral research associate and head of education at the Center for Leadership in the Future of Work at the University of Zurich. Hausfeld earned her PhD in organisational science from the University of North Carolina at Charlotte.

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Xbox Project Helix console could ditch the disc drive and go fully digital

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Xbox’s next-gen console might be going fully digital. And if the latest leaks are accurate, Microsoft could finally be preparing the move it almost made more than a decade ago… before the internet collectively lost its mind.

Could Xbox Project Helix completely ditch physical discs?

According to a new report from Windows Central, Xbox is reportedly working on something called “Project Saluki,” which appears to be a new Game Pass initiative designed specifically for the Chinese market. While details remain limited, the report suggests it could involve multiple regional Game Pass tiers and reward systems tailored around China’s unique gaming regulations, spending habits, and player preferences. Considering how important cloud gaming and subscription-based access have become in China, this could be part of a much bigger push for Xbox in the region.

That said, the more interesting part of the report revolves around references discovered inside the Xbox PC app pointing toward a mysterious “Positron” initiative tied to a possible Disc-to-Digital system. Naturally, this has sparked speculation that Microsoft’s upcoming next-gen console, currently known as Project Helix, could launch without a built-in disc drive altogether.

The leaked references suggest Microsoft may be exploring a way for physical game discs to be converted into digital licenses tied to a user’s Xbox account. If true, the idea seems aimed at easing players into an all-digital future without completely abandoning existing physical libraries overnight. Interestingly, Microsoft explored similar concepts during the Xbox One era, but backlash around digital ownership and always-online systems forced the company to back away at the time. The difference now is that the market has changed dramatically, with digital purchases and subscription gaming becoming the norm for a huge portion of console players.

And honestly, Microsoft has been building toward this for years anyway. The Xbox Series S launched as a fully digital console back in 2020, followed by the all-digital white Xbox Series X refresh in 2024. At this point, a disc-less Project Helix would feel less like a surprise and more like the next logical step in Xbox’s long-term Game Pass-focused strategy.

Project Helix may finally push Xbox into its all-digital era

Reports around Project Helix already suggest Microsoft is positioning the next Xbox more like a hybrid gaming platform, blending console simplicity with PC-style flexibility through support for Xbox libraries, Windows features, Steam, and cloud gaming. In that kind of ecosystem, physical discs start feeling increasingly outdated. Even PlayStation reportedly now sees most game sales happening digitally, while Xbox has spent years pushing Game Pass, Cloud Gaming, and Play Anywhere.

Ironically, Microsoft almost tried this exact shift back during the Xbox One era, when digital licenses and always-online requirements triggered massive backlash. But the market has changed dramatically since then. Today, most players already buy their games digitally, which makes a disc-less future feel far more realistic. It would not be surprising if both Xbox and Sony eventually ship fully digital next-gen consoles, potentially with optional external disc drives similar to the PS5 setup. The difference is that Sony benefits from Blu-ray ownership, while Xbox would still have to deal with licensing costs.

Of course, players are not exactly going to celebrate the death of physical games overnight. Going digital is easy for Microsoft. Convincing gamers that they are not losing ownership, flexibility, or preservation in the process is the harder part, especially at a time when Xbox is already trying to rebuild momentum against Sony. That said, these leaks are still very early, and even the original report suggests details are still being pieced together, so for now, this entire situation should be taken with a healthy amount of caution.

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European Union moves to crack down on addictive social media designs targeting children

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Von der Leyen stated that the EC – one of the European Union’s highest governing bodies – is taking action against TikTok and Meta’s social media platforms, including Facebook and Instagram. The video-sharing platform and Meta’s services are said to rely on engagement-driven features such as endless scrolling, auto-play, and…
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John Roberts Is The Driver Who Wants Credit For All The People He Didn’t Run Over

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from the unkicked-puppies dept

John Roberts has a point: the Supreme Court—even this Supreme Court—sometimes gets things right. Maybe one could even fairly say it often gets things right. After all, just recently it produced good decisions in Case v. Montana, Cox v. Sony, and First Women’s Choice Centers v. Davenport, and arguably even Chiles v. Salazar, along with plenty more that have quietly taken their place in the annals of American jurisprudence with little fanfare but the staying power we look to the Court’s opinions for, to continue to speak well into the future about the contours of our law. These were decisions where there was significant accord among all the justices because the legal questions before them were just not that hard to resolve. Either statutory language, constitutional text, or previous precedent required certain results, and Roberts is correct: this Court is fully capable of producing them.

The issue, however, is that it doesn’t always. And when it doesn’t it is not because it’s getting tripped up by close calls where either the precedent or guiding text isn’t clear, or the facts are so unfortunate that they obscure what the law requires. The issue is that the law is as equally clear in cases where the Court produces deviant results as in the cases where the Court gets things right; it just doesn’t care to follow it consistently. If it wants a different result than what the law directs then that is the result it will find the votes for.

Roberts is of course also right that non-lawyers often can’t tell what the law indeed requires; the general public is much more likely to judge a decision based on how it affects the interests they favor. Which is why Roberts has a fair point to think the Court may be unfairly criticized in decisions like Chiles, First Women’s Choice Centers, or even 303 Creative, cases where interests many understand to be harmful to others nevertheless apparently prevailed. It is difficult, for instance, for non-lawyers to see how a win for those who discriminate is nevertheless a win for those who are discriminated against, because while a win for the former may seem like a loss for the latter in the short term, it’s the rationale being upheld by the decision that will ultimately amount to a more important gain for the vulnerable in the long term.

But one reason people are struggling to see these controversial but correct decisions as fortifications of their own future freedom is because they don’t believe that when their interests are at stake the Supreme Court will still apply the same principles this time in their favor. They fear that the Court will instead find a way to advance the interests it prefers, and it’s a fear that is eminently reasonable. The hypocrisy the justices regularly display in their jurisprudence when one of their favored interests is at stake forecloses any rational person having any faith in them as neutral jurists ably applying the law, even if it’s true that sometimes they are.

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Roberts only has himself and his Court to blame for so many having that view. They have made it impossible for anyone to believe the Court will uphold principle and precedent because of how often it has not. It is happy to change the rules that we must all play by whenever it suits it, redrawing the rights we depend on as well as the ability to use the courts to shape them. And it’s not just laypeople who’ve noticed the problem but legal professionals. It’s lawyers, including members of the Supreme Court Bar who practice before them. It’s law professors, including those who have been teaching new generations of law students what were supposed to be timeless principles of American jurisprudence, which the Court so regularly and casually upends. It’s legal commentators, including those who specialize in watching this court. It is people who are experienced, if not expert—and if not at least as expert as anyone on the Court—in the American legal tradition who are calling foul. They are noticing how the Court keeps inventing arbitrary and imaginary rules, if not also facts, in order to arrive not where the law points but where the conservative justices steering the Court’s majority instead prefer to go.

It might be one thing if it were the rare case here and there in its busy docket where the Court has simply been sloppy in its jurisprudence. But the cases where the conservative majority has refused to produce jurisprudentially conservative results, instead elevating preferred outcomes over precedential reasoning, are hardly the exception; at this point it has become the apparently deliberate rule that when certain issues are on the table—partisan politics, reproductive freedom, LGBTQ+ rights, race relations, to name just a few areas where the conservative justices have particularly strong views—the Roberts Court will eagerly jump in to advance them, regardless of whether either substance or procedure—or consistency—even invites such an intervention, let alone their favored result. In fact it is fairly shocking to encounter the rare occasion where the Court has instead restrained itself—although it is certainly glad to when other interests the conservative majority is less dogmatically interested in advancing are instead on the table.

Furthermore, that its docket is so busy is entirely because the Court has abdicated any pretense of restraint, greedily helping itself to matters that historically would have been regarded as unripe for its consideration. In fact, it is a bit rich for Roberts to complain how the Supreme Court is being unfairly disrespected given the extent to which its new practice of aggressively insinuating itself in substantive adjudication of matters before there even is a lower court ruling or record ready for review has itself undercut the respect due the lower courts. What the Court has been doing, particularly with its Shadow Docket, goes far beyond the appellate review it is normally entitled to do. Not only does the Supreme Court’s incessant snatching of matters away from the lower courts prematurely arbitrarily diminish the lower courts’ power to render considered opinions on the questions before them, but it has also been having the practical effect of undermining their ability to speak with any authority on the law at all, let alone enforce it. Would only Roberts shed the same tears for the insult the lower courts have actually suffered as he does for himself as the cause of it.

Instead, and apparently without any capacity for introspection or self-reflection, he protests that the criticism increasingly directed at the Court is not also increasingly deserved. We should, he insists, be judging his Court based on what it gets right. But we do not celebrate a reckless driver for all the people he didn’t run over, or careless chef for all the diners he didn’t poison, or distracted doctor for all the patients he didn’t kill. In the American legal tradition we judge harshly those who cause injury to the public well-being, especially with behavior beyond the bounds of what law allows.

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And with the Roberts Court there is so much to judge.

Filed Under: consistency, john roberts, partisanship, supreme court

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Apple TV exec leaving to start his own production company

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Morgan Wandell, who has been with Apple TV since before its launch, is now departing the streaming service in favor of launching his own production company.

In 2017, Apple poached Wandell from Amazon Studios to join its team at Apple Worldwide Video. When Apple TV launched in 2019, his title became Head of International Content Development.

While at Apple, Wandell developed and oversaw production of “Monarch: Legacy of Monsters,” “Tehran,” “Disclaimer,” “Masters of the Air,” and “The New Look.”

Now, it seems as though he’s got other plans. Wandell plans on leaving Apple TV to found his own production company, Kismet.

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Kismet will develop and produce premium scripted series for the global marketplace. Its offerings will focus on high-end culturally rooted storytelling.

While he is technically leaving his executive role behind, it seems that he may not be leaving Apple TV entirely. He’s currently in talks with Apple to stay on as a producer on some of his existing projects.

“Helping to build Apple TV’s international slate has been the privilege of my career,” Wandell told Deadline.

“I’m deeply grateful to Jamie [Erlicht], Zack [Van Amburg], and all my colleagues at Apple, and to the extraordinary creators we’ve partnered with around the world. It was a hard personal decision to make this leap from a company as terrific as Apple, but I have always wanted to build a company of my own.”

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Matt Cherniss, Apple TV’s Head of Programming and Domestic Development, will take over the Monarch franchise and other series that were under Wandell’s purview. Cherniss currently oversees other hit series, such as “Ted Lasso,” “Severance,” “The Studio,” and “Pluribus.”

Jay Hunt, Apple TV’s creative director, Europe, will see her role expand to oversee international and local-language originals. She is in charge of British staples “Slow Horses” and “Hijack”, among others.

Before his tenure at Apple, Wandell worked as Head of International Series and Head of Drama Series at Amazon Studios for four years. Before that, he acted as Senior Vice President of Drama at ABC studios, overseeing series including “Lost,” “Grey’s Anatomy,” “Brothers and Sisters,” “Ugly Betty,” and “Criminal Minds.”

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Microsoft reveals another way it’s making Windows 11 faster, with more performance boosts promised for the likes of File Explorer

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  • Microsoft is working to make WinUI 3 speedier
  • This is the contemporary framework for the user interface of the OS
  • With WinUI 3 being employed more widely across Windows 11, and tweaked for better performance, it’s another key way in which the OS could be made faster

We’ve learned more about Microsoft‘s efforts to make Windows 11 faster, discovering another front that the company is working on to ensure the operating system becomes more performant in terms of core interface elements.

Windows Central reports that the big drive for better performance — which is part of the broader campaign to fix Windows 11 — doesn’t just involve transitioning elements of the Windows 11 interface to use WinUI 3, but actually speeding up WinUI itself.

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AI customer service bots get rolled back at 74% of firms

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AI rollback rates hit 81% at firms with mature guardrails, suggesting enterprises are struggling to manage the systems in production, says Sinch

If you’re thinking you can replace your human call center staff with a server farm of bots, think again. Nearly three-quarters of enterprises that deploy AI customer communications agents later roll them back or shut them down, according to new research suggesting the systems are far harder to manage reliably in production than the AI hype implied.

Swedish comms-as-a-service firm Sinch surveyed more than 2,500 AI decision makers from various countries and industries for its AI Production Paradox study. The starkest finding is undoubtedly the 74 percent rollback or shutdown rate for deployed AI customer communications agents tied to governance failures, but that’s not the only sign enterprise AI deployments are falling short of expectations. 

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AI rollback rates, which Sinch told us specifically refer to AI projects that were deployed and pulled from live service rather than projects that failed before launch, actually rise to 81 percent among organizations that it describes as having “fully mature guardrails.” That, says Sinch Chief Product Officer Daniel Morris, suggests governance alone is not fixing the problem. 

“The most advanced organizations aren’t failing less; they’re seeing failures sooner. Higher rollback rates reflect better monitoring and control, not weaker performance,” Morris said in a press release. “If governance was the fix, the most mature teams would roll back less, not more. Our data points to a deeper issue.”

According to the findings, 84 percent of AI engineering teams are spending at least half their time on safety infrastructure, leaving little time to develop AI. This is exacerbated by the fact that most firms said spending on AI trust, security, and compliance ranks ahead of AI development itself.

“When 75% put trust, security, and compliance in that top three — ahead of AI development itself at 63% — that’s a finding about where the priority sits within their AI customer communications programs,” a Sinch spokesperson told us in an email. In other words, it seems like most organizations realize that their biggest issue with AI isn’t getting it working properly – it’s getting it to just work safely in the first place. 

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“The operational cost of running AI safely at scale is much larger than most organizations expect,” the Sinch representative explained.

The numbers don’t change based on organizational size or budget, either, Sinch told us. 

“The rollback rate holds consistently across every region and every industry in the study, which suggests size isn’t a meaningful protective factor,” the company said. “Rollback isn’t a symptom of under-investment or being too small to afford proper guardrails.” 

Of course, as a business communications service provider, Sinch linked its results back to AI customer service agents not being properly deployed on comms infrastructure designed for AI agents, a problem it’s naturally positioned to offer a fix for. 

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Regardless, that three-quarter rollback figure doesn’t seem too out of place when you consider recent customer service automation news. 

As we’ve reported on multiple occasions, replacing customer service staff with AI hasn’t gone to plan for many businesses. Gartner said in June 2025 that half of organizations expecting AI to significantly reduce customer service headcount would abandon those plans by 2027. Sinch’s numbers suggest the problem may extend beyond staffing cuts to the AI agents themselves. Not that far-fetched when Gartner was already warning last year that fully agentless contact centers were not practical in the real world.

“Our vendor evaluations reveal that a agentless contact center is not yet technically feasible, nor is it operationally desirable,” Brian Weber, VP analyst in the Gartner Customer Service & Support practice, told The Register, adding that unexpected costs and unintended results were contributing to abandonment plans – just like what Sinch is reporting now. ®

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OpenAI Brings Its Ass to Court

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Wednesday’s episode of the Musk v. Altman trial kicked off on Wednesday with a unique proposition: OpenAI wanted to bring its ass into the courtroom, and lay it bare before the jury. It’s a good thing lady justice wears that blindfold.

A lawyer for Sam Altman’s AI behemoth, Bradley Wilson, approached US district judge Yvonne Gonzalez Rogers and handed her a small gold statue with a white stone base. It depicted the rear end of a donkey—with two legs, a butt, and a tail—and was inscribed with the message, “Never stop being a jackass for safety.”

OpenAI lawyers claim a small group of employees presented the gift to chief futurist Joshua Achiam, who started at the company as an intern in 2017 and now leads its work studying how society is changing in response to AI. Wilson said that Achiam interrupted Elon Musk’s parting speech from OpenAI in 2018 to warn that the billionaire’s desire to develop AGI at Tesla could come at the expense of safety. Wilson added that the trophy commemorates some “strong language” that Musk used toward Achiam in response—allegedly, calling him a jackass.

OpenAI requested to present the physical object during Achiam’s testimony on Wednesday, arguing that it adds to their case. While Musk’s team said the statue was irrelevant, Judge Gonzalez Rogers said she will consider allowing it when it’s referenced to corroborate the story. However, she seemed less than thrilled about accepting it as official evidence, which would put it in the court’s possession. “I don’t want it,” she said.

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Representatives for Musk and OpenAI did not immediately respond to a request for comment about the ass.

Musk’s lawsuit accuses OpenAI of effectively stealing a charity, misusing his $38 million in donations to build an $850 billion business. In response, OpenAI has argued that Musk has always cared more about controlling a top-tier AGI lab than funding a nonprofit.

Earlier in the trial, Musk lawyer Steven Molo asked him if he ever called an OpenAI employee a “jackass.” Musk said “it’s possible” he did at some point, but that he didn’t mean for it to be offensive. “Sometimes you have to use language that gets people out of their comfort zone, if we’re going in the wrong direction,” Musk said.

OpenAI has long been proud of its jackass. When The Wall Street Journal asked about the statue in 2023, Altman told them, “You’ve got to have a little fun … This is the stuff that culture gets made out of.”

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Harvard Votes On Limiting ‘A’ Grades

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Harvard faculty are voting on a proposal (PDF) to curb grade inflation by limiting solid A grades to 20% of students in a class, plus four additional A’s per course. Axios reports: Grade inflation is at a tipping point at Harvard. A move to make A grades harder to come by at one of the world’s leading universities could influence grading debates at peer institutions. Solid A’s account for nearly two-thirds of all undergraduate letter grades. That’s up from roughly a quarter 20 years ago. More than 50 members of last year’s class graduated with perfect GPAs.

[…] Faculty are voting on three separate provisions. Each requires a simple majority to pass. A cap to limit solid-A grades to 20% of enrolled students in a class, plus four additional A’s per course. Changes to how internal honors are calculated, moving from traditional grade point average scoring to an average percentile rank. Allowing courses to use new “satisfactory” or “unsatisfactory” marks with a “satisfactory-plus” distinction.

A pre-vote faculty poll showed around 60% of the 205 respondents favored the 20-plus-four formula over an alternative. Supporters of the cap argue it’s intentionally modest as it places no restrictions on A-minuses. The four-grade buffer is designed to protect small seminars where a higher proportion of students may succeed. […] If passed, changes would take effect in fall 2027, followed by a mandatory three-year review.

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