Category: English

Source: The Conversation – USA – By Ambuj Tewari, Professor of Statistics, University of Michigan

You’ve just finished a strenuous hike to the top of a mountain. You’re exhausted but elated. The view of the city below is gorgeous, and you want to capture the moment on camera. But it’s already quite dark, and you’re not sure you’ll get a good shot. Fortunately, your phone has an AI-powered night mode that can take stunning photos even after sunset.

Here’s something you might not know: That night mode may have been trained on synthetic nighttime images, computer-generated scenes that were never actually photographed.

As artificial intelligence researchers exhaust the supply of real data on the web and in digitized archives, they are increasingly turning to synthetic data, artificially generated examples that mimic real ones. But that creates a paradox. In science, making up data is a cardinal sin. Fake data and misinformation are already undermining trust in information online. So how can synthetic data possibly be good? Is it just a polite euphemism for deception?

As a machine learning researcher, I think the answer lies in intent and transparency. Synthetic data is generally not created to manipulate results or mislead people. In fact, ethics may require AI companies to use synthetic data: Releasing real human face images, for example, can violate privacy, whereas synthetic faces can offer similar benefit with formal privacy guarantees.

There are other reasons that help explain the growing use of synthetic data in training AI models. Some things are so scarce or rare that they are barely represented in real data. Rather than letting these gaps become an Achilles’ heel, researchers can simulate those situations instead.

Another motivation is that collecting real data can be costly or even risky. Imagine collecting data for a self-driving car during storms or on unpaved roads. It is often much more efficient, and far safer, to generate such data virtually.

How synthetic data is made

Training an AI model requires large amounts of data. Like students and athletes, the more an AI is trained, the better its performance tends to be. Researchers have known for a long time that if data is in short supply, they can use a technique known as data augmentation. For example, a given image can be rotated or scaled to yield additional training data. Synthetic data is data augmentation on steroids. Instead of making small alterations to existing images, researchers create entirely new ones.

But how do researchers create synthetic data? There are two main approaches. The first approach relies on rule-based or physics-based models. For example, the laws of optics can be used to simulate how a scene would appear given the positions and orientations of objects within it.

The second approach uses generative AI to produce data. Modern generative models are trained on vast amounts of data and can now create remarkably realistic text, audio, images and videos. Generative AI offers a flexible way to produce large and diverse datasets.

Both approaches share a common principle: If data does not come directly from the real world, it must come from a realistic model of the world.

Downsides and dangers

It is also important to remember that while synthetic data can be useful, it is not a panacea. Synthetic data is only as reliable as the models of reality it comes from, and even the best scientific or generative models have weaknesses.

Researchers have to be careful about potential biases and inaccuracies in the data they produce. For example, researchers may simulate the home-insurance ecosystem to help detect fraud, but those simulations could embed unfair assumptions about neighborhoods or property types. The benefits of such data must be weighed against risks to fairness and equity.

It’s also important to maintain a clear distinction between models and simulations on one hand and the real world on the other. Synthetic data is invaluable for training and testing AI systems, but when an AI model is deployed in the real world, its performance and safety should be proved with real, not simulated, data for both technical and ethical reasons.

Future research on synthetic data in AI is likely to face many challenges. Some are ethical, some are scientific, and others are engineering problems. As synthetic data becomes more realistic, it will be more useful for training AI, but it will also be easier to misuse. For example, increasingly realistic synthetic images can be used to create convincing deepfake videos.

I believe that researchers and AI companies should keep clear records to show which data is synthetic and why it was created. Clearly disclosing which parts of the training data are real and which are synthetic is a key aspect of responsibly producing AI models. California’s law, “Generative artificial intelligence: training data transparency,” set to take effect on Jan. 1, 2026, requires AI developers to disclose if they used synthetic data in training their models.

Researchers should also study how mistakes in simulations or models can lead to bad data. Careful work will help keep synthetic data transparent, trustworthy and reliable.

Keeping it real

Most AI systems learn by finding patterns in data. Researchers can improve their ability to do this by adding synthetic data. But AI has no sense of what is real or true. The desire to stay in touch with reality and to seek truth belongs to people, not machines. Human judgment and oversight in the use of synthetic data will remain essential for the future.

The next time you use a cool AI feature on your smartphone, think about whether synthetic data might have played a role. Our AIs may learn from synthetic data, but reality remains the ultimate source of our knowledge and the final judge of our creations.

Ambuj Tewari receives funding from NSF and NIH.

– ref. When fake data is a good thing – how synthetic data trains AI to solve real problems – https://theconversation.com/when-fake-data-is-a-good-thing-how-synthetic-data-trains-ai-to-solve-real-problems-265180

Source: The Conversation – USA (2) – By Antar A. Tichavakunda, Associate Professor of Education, University of California, Santa Barbara

Black student unions have been a vital part of many Black college students’ lives for more than 60 years. But since 2024, Black student unions have lost their institutional support, campus space and funding with the rise of anti-diversity, equity and inclusion laws in Utah and Alabama.

Black student unions now face a new wave of pressure, as more than 400 colleges and universities under the Trump administration have rebranded or eliminated programs and centers that promote diversity, equity and inclusion.

Amy Lieberman, education editor at The Conversation U.S., spoke with Antar A. Tichavakunda, a scholar of race and higher education, to better understand what Black student unions are and how they influence Black students’ experiences in higher education.

Why are Black student unions important, particularly for Black students?

Aside from Black fraternities and sororities, Black student unions were among the first ethnic student organizations at colleges to be established. A group of students started the first Black student union in 1968 at San Francisco State University. This happened during the Black Campus Movement, when Black college students advocated for themselves, making demands for resources, respect, spaces and programs to support Black student life. At the time, Mariana Waddy, a student at San Francisco State University and the first president of a Black student union, said, “This college had done little for Black students except try to whitewash them.”

Black students wanted to make the school more engaging and responsive to their needs.

Today, these student unions are essential for Black student life on college campuses. They offer a place of belonging, where Black students can figuratively exhale from a predominately white campus or student environment. Black student life on campus isn’t a given – just because there are Black students, it doesn’t mean there is a Black student community. These unions allow Black students to come together as a community.

What do these unions look like and do, day to day?

Black student unions largely operate independently. They have various events, like cookouts and parties. If a campus is dealing with an issue or some kind of racist occurrence, for example, Black student union leaders will come to the forefront to be an advocate for Black students. They try to engage with students and university leaders on whatever is happening.

How are political pressure and policy shifts influencing these unions?

The University of Utah and the University of Alabama announced in 2024 that they would no longer fund or support their schools’ Black student unions. Universities typically give these unions a certain amount of money, as they do with other student-led groups. With this funding pulled, it is going to make it harder for Black student unions to exist. Where are they going to meet? Will they have to pay for a place to meet off campus?

And if you want to encourage students to come to Black student events, you will likely want to have food for them. If you want to arrange a trip to a conference or host a movie night, those things cost money and require space.

These cuts have drained time, energy and resources from Black student unions.

Now, Black student leaders are filling gaps where funding, staff, spaces and infrastructure used to exist to support and meet the needs of Black student life.

The Trump administration’s attempts to remove funding from and shut down diversity, equity and inclusion programs could lead Black student union leaders to act as unpaid diversity workers if and when these positions at universities are eliminated.

This work also involves organizing social events and support services for Black students. It means continuing to creatively advocate for Black student needs.

Full-time students leading Black student unions now find themselves doing unpaid labor that helps sustain Black communities and the universities that profit from them.

How exactly are universities profiting from Black student unions’ work?

Here’s one example: I observed a university tapping student leaders from a Black engineering group to represent the university’s school of engineering at public events. These leaders might have had to skip class or lose study time to be available for this event. But the university wanted other people, including prospective Black students, to know that there were already Black students at this school.

Black students in these positions have mentioned to me that sometimes administrators will pressure them to show up for panels and other events as a form of marketing. I think most of these requests are well-meaning. But I also know that Black student representatives and leaders place pressure on themselves to also show up for their community and school.

Their presence and visibility help universities have a more welcoming environment. They have an active, vibrant community because of Black student unions and leaders. Organizations like this create community and lead to more positive experiences for students. This joy can lead to more students staying in school.

If I am a Black parent touring a college with my child and don’t see any Black students participating in the tour or on campus, that sends a message to a prospective Black student – will I, or my child, belong here?

What message are Black student unions receiving with these policy shifts?

I think the message to Black student unions is that you all have to fend for yourselves. That is what inequality is all about, having different expectations for different students.

Cuts to diversity, equity and inclusion work signals to Black students that they are not valued and that, if they want to have meaningful experiences as a Black student community, they will have to do this work themselves. You can discern an institution’s values in their budget priorities. If there is nothing being materially invested in Black students, how can you say you support them?

My research shows that Black students act independently to achieve their goals. They create places of joy and belonging for themselves and others, navigating institutions to create full, dynamic lives.

Black students have historically played the cards they were dealt, even if they were inequitable. They have worked to create traditions and lives within and outside of higher education’s campus walls. Some Black student unions may look different going forward, but I have full faith they will continue.

Antar A. Tichavakunda does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Black student unions are under pressure – here’s what they do and how they help Black students find community – https://theconversation.com/black-student-unions-are-under-pressure-heres-what-they-do-and-how-they-help-black-students-find-community-268754