By Cyril Ramaphosa

Last week, Minister of Finance Enoch Godongwana presented a Budget that will accelerate the momentum of inclusive growth, create jobs and tackle poverty.

Every budgetary allocation is a developmental choice: ensuring there are teachers in classrooms, nurses and doctors in clinics, electricity and basic services in homes and businesses, infrastructure to grow the economy, and employment opportunities for communities.

After a prolonged period of economic uncertainty, this Budget builds on the progress made over the last few years to stabilise, reform and transform our economy. Improvements in public finances, stabilising debt, a narrowing budget deficit, credit rating upgrades and improved market confidence all signal the beginning of an economic recovery.

A stable macroeconomic environment boosts investor confidence and increases government’s capacity to invest in both growth and poverty relief without compromising sustainability.

The stabilisation of public finances gives us space to accelerate public investment, sustain the social wage, and direct resources to reforms that drive growth and job creation.

The social wage accounts for over 60% of government spending after interest payments. The allocation for this financial year will enable us to provide healthcare services to 84% of the population, social grants to 26.5 million beneficiaries and free basic services to over 11 million indigent households. It will support approximately 13.6 million learners at school.

This is a redistributive budget that reduces inequality, builds the capabilities of our people and strengthens the foundations for inclusive growth.

Basic education is one of those key foundations. We will be allocating additional spending to employ more educators. Additional funds have been allocated to the early childhood development grant to reach an additional 300,000 children and to align the National School Nutrition Programme to food inflation.

The Budget supports inclusive growth by accelerating public investment, particularly on infrastructure. Improved infrastructure lowers the cost of doing business, raises productivity and supports our country’s exports.

Over the next three years, public spending on infrastructure will exceed R1 trillion to build and maintain roads and rail lines, expand energy infrastructure, and build and maintain water and sanitation infrastructure.

Government alone cannot finance the scale of infrastructure our country needs. We are therefore mobilising investment from private and other sources, and opening the space for public-private partnerships. As we encourage private investment in electricity, rail and port operations, we are maintaining state ownership of strategic national infrastructure.

Under Operation Vulindlela, government departments and public entities are undertaking impactful reforms in energy, telecommunications, water and logistics.

The Budget acknowledges that many municipalities are in financial distress, driven by weak revenue collection, poor management and substantial service delivery backlogs.

Many municipalities are not spending appropriately. For several years, water and electricity revenue has not been invested in infrastructure maintenance or expansion, but has been redirected to cover other municipal costs.

Local government finances have to be placed on a more sustainable footing to support the delivery of basic services. Over the medium term, R19.2 billion will be reallocated to the reform of electricity, water, sanitation and solid waste trading services in metros. These allocations will be linked to performance against clear targets.

The Municipal Infrastructure Grant is being reformed to address underspending and misuse of funds. Over the next three years, R86.9 billion has been allocated to support the provision of free basic services to indigent households.

This year’s budget reflects government’s goals of inclusive growth and job creation through additional support for mass public employment programmes and relief for small businesses.

An additional R4.1 billion has been allocated to the Presidential Employment Stimulus to provide work opportunities to more young South Africans.

To ease the regulatory burden for small businesses, the threshold for businesses to register for VAT has been more than doubled. For small business owners who wish to sell or transfer their businesses, the capital gains tax exemption has also been significantly increased.

Together, these measures will help small and informal businesses to grow and employ more South Africans.

This year’s Budget focuses on three imperatives: maintaining fiscal sustainability, driving inclusive growth and protecting society’s most vulnerable. It is a balanced budget that reflects the realities of our economy, limited financial resources, high unemployment and urgent infrastructure needs.

As we build on the momentum of our recovery, we will continue to be guided by fiscal discipline, structural reform, targeted investment and an overarching commitment to improving the material conditions of every South African.

Cyril Ramaphosa is President of South Africa.

INSIDE EDUCATION

By Charmaine Ndlela

The Chairperson of the Portfolio Committee on Higher Education and Training, Tebogo Letsie, has called for the dismissal of the University of the Witwatersrand (Wits) Head of Sociology, Professor Srila Roy, following a controversial social media post that sparked national outrage.

Roy resigned as Head of the Department of Sociology after posting on her personal X account that South Africans “have little ambition, are complacent and have a poor work ethic”.

The remarks were made during a debate about foreign academics in South African universities and drew fierce criticism from students, academic groups and political figures.

The university has since placed her on precautionary suspension pending the outcome of an investigation.

Her resignation was confirmed by the Sociology Department on 26 February, and the investigation continues in line with Wits policies.

The saga has triggered debate about academic accountability, discrimination and the role of social media conduct by academics.

The South African Sociological Association condemned her comments, describing them as classist, racist and xenophobic, and said they contradicted the principles and values of South African higher education.

Letsie described the remarks as unacceptable and said such conduct should not be tolerated in the higher education sector.

“Her remarks were offensive, derogatory and undermined the dignity of many South Africans. Such views are completely unacceptable, especially from someone entrusted with teaching and leading in our universities. This is not a minor matter,” he said.

“These statements reflect deeply troubling views that cannot simply be overlooked.”

Letsie said the matter warrants serious consequences and that a demotion would not constitute sufficient accountability.

He said dismissal would be the appropriate sanction should the allegations be substantiated.

“We cannot tolerate individuals who openly express views that are widely regarded as discriminatory and then expect to continue shaping young minds and leading academic departments,” he added.

He said Wits leadership’s swift response demonstrates the seriousness of the matter, noting it would be untenable for a head of department to remain in position if their conduct is found to be inconsistent with institutional values.

“Leadership must reflect the values of equality, fairness and respect,” he said.

Letsie further stated that the committee has received information from members of the university community and the public raising concerns about fairness and equal opportunity.

“There are allegations that South Africans may have been unfairly excluded from opportunities in her department. These allegations must be fully investigated,” he said.

“Our universities must never be used to advance exclusion or discrimination.”

He emphasised that accountability must be decisive.

“We are determined to restore integrity, fairness and accountability. No one is above scrutiny. Our higher education institutions must remain spaces of dignity, fairness and transformation for all South Africans,” he said.

Roy issued an apology on 23 February, saying her comments were a “hasty pushback against xenophobic attitudes”.

“I fully understand that the tweet caused hurt, and I sincerely regret and apologise for it. Given South Africa’s painful history of racist stereotyping, the tweet was wrong, and I take full responsibility for the pain it has caused,” she said.

She stressed that the post was not intended to express derogatory views about South Africans or South African academics.

“I want to be clear that I do not hold such views. My academic work, committee contributions, supervision and mentoring reflect this,” she said.

“Despite the context of academic xenophobia, my response was not acceptable. I exercised poor judgment and take full responsibility,” she wrote.

INSIDE EDUCATION

By Thapelo Molefe

Basic Education Minister Siviwe Gwarube has officially launched her bid for the position of Deputy Federal Chairperson of the Democratic Alliance (DA) ahead of the party’s federal elective congress in April.

Gwarube confirmed her candidacy on her social media platforms on Monday, ending weeks of speculation regarding her move into the party’s top federal structure. 

“Yes it is true, I am running! Democrats, I am happy to announce that I have accepted the nomination for Deputy Federal Chairperson,” she wrote on her X account.

Gwarube framed her candidacy as a strategic necessity for the party’s national ambitions. 

“The truth is simple: we need to be the largest party in South Africa in order to bring the change so desperately needed in our country,” she said. 

Her campaign emphasises the need for a leadership core capable of organising and expanding support across every province and community.

Gwarube’s platform is built on the premise that internal electoral growth is the primary driver of national political change, asserting that “only a growing DA can deliver a growing SA.” 

By specifically contesting the “number one” deputy spot, Gwarube is positioning herself as the most senior of the three deputy chairs typically elected, a role that serves as a critical bridge between the federal executive and grassroots structures.

The announcement comes as the DA prepares for its elective congress, taking place in April in Gauteng. The party is facing a significant leadership transition following the announcement that Federal Leader John Steenhuisen will not seek re-election earlier last month.

Gwarube has seen a rapid rise within the DA since entering Parliament in 2019.

She has served as national spokesperson, deputy chief whip, and chief whip before her 2024 appointment as Minister of Basic Education within the Government of National Unity (GNU).

Her international profile was further elevated in 2025 when she was selected for the World Economic Forum’s Young Global Leaders programme.

As a prominent figure in the party’s reformist wing, Gwarube’s entry adds further weight to a leadership race that includes Cape Town Mayor Geordin Hill-Lewis, who is running for Federal Leader, and Gauteng leader Solly Msimanga, who is contesting the Federal Chairperson position.

The nominations window for leadership positions remains open until March 23, 2026. The results of the April congress are expected to define the leadership team that will steer the DA into the next general election cycle.

INSIDE EDUCATION

By Nir Eisikovits and Jacob Burley

Public debate about artificial intelligence in higher education has largely orbited a familiar worry: cheating. Will students use chatbots to write essays? Can instructors tell? Should universities ban the tech? Embrace it?

These concerns are understandable. But focusing so much on cheating misses the larger transformation already underway, one that extends far beyond student misconduct and even the classroom.

Universities are adopting AI across many areas of institutional life. Some uses are largely invisible, like systems that help allocate resources, flag “at-risk” students, optimize course scheduling or automate routine administrative decisions. Other uses are more noticeable. Students use AI tools to summarize and study, instructors use them to build assignments and syllabuses and researchers use them to write code, scan literature and compress hours of tedious work into minutes.

People may use AI to cheat or skip out on work assignments. But the many uses of AI in higher education, and the changes they portend, beg a much deeper question: As machines become more capable of doing the labor of research and learning, what happens to higher education? What purpose does the university serve?

Over the past eight years, we’ve been studying the moral implications of pervasive engagement with AI as part of a joint research project between the Applied Ethics Center at UMass Boston and the Institute for Ethics and Emerging Technologies. In a recent white paper, we argue that as AI systems become more autonomous, the ethical stakes of AI use in higher ed rise, as do its potential consequences.

As these technologies become better at producing knowledge work – designing classes, writing papers, suggesting experiments and summarizing difficult texts – they don’t just make universities more productive. They risk hollowing out the ecosystem of learning and mentorship upon which these institutions are built, and on which they depend.

Nonautonomous AI

Consider three kinds of AI systems and their respective impacts on university life:

AI-powered software is already being used throughout higher education in admissions review, purchasing, academic advising and institutional risk assessment. These are considered “nonautonomous” systems because they automate tasks, but a person is “in the loop” and using these systems as tools.

These technologies can pose a risk to students’ privacy and data security.

They also can be biased. And they often lack sufficient transparency to determine the sources of these problems. Who has access to student data? How are “risk scores” generated? How do we prevent systems from reproducing inequities or treating certain students as problems to be managed?

These questions are serious, but they are not conceptually new, at least within the field of computer science. Universities typically have compliance offices, institutional review boards and governance mechanisms that are designed to help address or mitigate these risks, even if they sometimes fall short of these objectives.

Hybrid AI

Hybrid systems encompass a range of tools, including AI-assisted tutoring chatbots, personalized feedback tools and automated writing support. They often rely on generative AI technologies, especially large language models. While human users set the overall goals, the intermediate steps the system takes to meet them are often not specified.

Hybrid systems are increasingly shaping day-to-day academic work. Students use them as writing companions, tutors, brainstorming partners and on-demand explainers. Faculty use them to generate rubrics, draft lectures and design syllabuses. Researchers use them to summarize papers, comment on drafts, design experiments and generate code.

This is where the “cheating” conversation belongs. With students and faculty alike increasingly leaning on technology for help, it is reasonable to wonder what kinds of learning might get lost along the way. But hybrid systems also raise more complex ethical questions.

One has to do with transparency. AI chatbots offer natural-language interfaces that make it hard to tell when you’re interacting with a human and when you’re interacting with an automated agent.

That can be alienating and distracting for those who interact with them. A student reviewing material for a test should be able to tell if they are talking with their teaching assistant or with a robot.

A student reading feedback on a term paper needs to know whether it was written by their instructor. Anything less than complete transparency in such cases will be alienating to everyone involved and will shift the focus of academic interactions from learning to the means or the technology of learning. University of Pittsburgh researchers have shown that these dynamics bring forth feelings of uncertainty, anxiety and distrust for students. These are problematic outcomes.

A second ethical question relates to accountability and intellectual credit. If an instructor uses AI to draft an assignment and a student uses AI to draft a response, who is doing the evaluating, and what exactly is being evaluated?

If feedback is partly machine-generated, who is responsible when it misleads, discourages or embeds hidden assumptions? And when AI contributes substantially to research synthesis or writing, universities will need clearer norms around authorship and responsibility – not only for students, but also for faculty.

Finally, there is the critical question of cognitive offloading. AI can reduce drudgery, and that’s not inherently bad. But it can also shift users away from the parts of learning that build competence, such as generating ideas, struggling through confusion, revising a clumsy draft and learning to spot one’s own mistakes.

Autonomous agents

The most consequential changes may come with systems that look less like assistants and more like agents.

While truly autonomous technologies remain aspirational, the dream of a researcher “in a box” – an agentic AI system that can perform studies on its own – is becoming increasingly realistic.

Agentic tools are anticipated to “free up time” for work that focuses on more human capacities like empathy and problem-solving. In teaching, this may mean that faculty may still teach in the headline sense, but more of the day-to-day labor of instruction can be handed off to systems optimized for efficiency and scale.

Similarly, in research, the trajectory points toward systems that can increasingly automate the research cycle. In some domains, that already looks like robotic laboratories that run continuously, automate large portions of experimentation and even select new tests based on prior results.

At first glance, this may sound like a welcome boost to productivity. But universities are not information factories; they are systems of practice.

They rely on a pipeline of graduate students and early-career academics who learn to teach and research by participating in that same work. If autonomous agents absorb more of the “routine” responsibilities that historically served as on-ramps into academic life, the university may keep producing courses and publications while quietly thinning the opportunity structures that sustain expertise over time.

The same dynamic applies to undergraduates, albeit in a different register. When AI systems can supply explanations, drafts, solutions and study plans on demand, the temptation is to offload the most challenging parts of learning. To the industry that is pushing AI into universities, it may seem as if this type of work is “inefficient” and that students will be better off letting a machine handle it.

But it is the very nature of that struggle that builds durable understanding. 

Cognitive psychology has shown that students grow intellectually through doing the work of drafting, revising, failing, trying again, grappling with confusion and revising weak arguments. This is the work of learning how to learn.

Taken together, these developments suggest that the greatest risk posed by automation in higher education is not simply the replacement of particular tasks by machines, but the erosion of the broader ecosystem of practice that has long sustained teaching, research and learning.

An uncomfortable inflection point

So, what purpose do universities serve in a world in which knowledge work is increasingly automated? One possible answer treats the university primarily as an engine for producing credentials and knowledge. There, the core question is output: Are students graduating with degrees? Are papers and discoveries being generated? If autonomous systems can deliver those outputs more efficiently, then the institution has every reason to adopt them.

But another answer treats the university as something more than an output machine, acknowledging that the value of higher education lies partly in the ecosystem itself.

This model assigns intrinsic value to the pipeline of opportunities through which novices become experts, the mentorship structures through which judgment and responsibility are cultivated, and the educational design that encourages productive struggle rather than optimizing it away.

Here, what matters is not only whether knowledge and degrees are produced, but how they are produced and what kinds of people, capacities and communities are formed in the process. In this version, the university is meant to serve as no less than an ecosystem that reliably forms human expertise and judgment.

In a world where knowledge work itself is increasingly automated, we think universities must ask what higher education owes its students, its early-career scholars and the society it serves. The answers will determine not only how AI is adopted, but also what the modern university becomes.

THE CONVERSATION