Communications and Digital Technologies Minister Solly Malatsi states that the future will not belong exclusively to artificial intelligence (AI), but rather to augmented intelligence, where AI serves to enhance human capabilities rather than replace them.
During a panel discussion at the Sixth Summit of Social Media Governments, the question was raised about what must remain uniquely human as AI capabilities grow. Although current discourse often focuses on AI's capabilities—data analysis, image recognition, content generation, and real-time translation—the discussion author believes the wrong question is being asked.
For a long time, debates were built on the assumption of competition between AI and human intelligence (HI), suggesting that the smarter machines become, the less valuable human intelligence becomes. However, the author believes the situation is the opposite. He cites historical tools such as calculators, GPS, and search engines, which did not make people less intelligent but allowed them to concentrate on more complex tasks.
Psychologists Evan Risko and Sam Gilbert call this phenomenon cognitive offloading—the deliberate use of external tools to reduce cognitive load while maintaining the ability to judge, create, and reason. Artificial intelligence is viewed as another chapter in this story.
Steven Shaw and Gideon Nave argue that the emergence of generative AI poses a new challenge they call cognitive abdication. The problem is not simply that people delegate cognitive tasks to technologies, but that they begin accepting machine-generated conclusions without proper verification or independent thought.
The author emphasizes the critical distinction: cognitive offloading is delegation, whereas cognitive abdication is renunciation. When using a calculator, a person delegates arithmetic but retains the right to decide if the answer makes sense. Similarly, when using GPS, a person remains responsible for assessing route safety, even if the technology performs the calculations.
Artificial intelligence only becomes problematic when we start delegating judgment itself. The main risk, according to scientists, is not that machines become smarter, but that people become less intellectually engaged by accepting algorithmic results without doubt, understanding, or contextualization.
History shows that society's greatest failures are rarely linked to a lack of information; more often, they are due to errors in judgment. No algorithm can understand legitimacy, no machine experiences empathy, and no model can weigh competing constitutional rights or assess the social consequences of a decision. AI can assess probabilities, but it cannot determine what should be done.
At Sasria, in collaboration with the Council for Scientific and Industrial Research (CSIR), predictive risk analytics systems are being developed. These systems combine machine learning, behavioral science, sentiment analysis, and geospatial intelligence to better understand emerging social threats. A 'Four Levels of Protection' model has been developed, designed not just to predict unrest, but to increase societal resilience against it.
The technology is capable of finding patterns in millions of data points, which is inaccessible to a single analyst. However, it cannot explain the meaning of these patterns. A rise in negative sentiment may indicate real social instability, political mobilization, or simply a temporary public reaction to an isolated event. The algorithm detects the signal, and human intelligence interprets the context, which is an example of augmentation, not replacement.
This is also an area where the study of hybrid intelligence intersects. The strongest results are achieved not when humans compete with AI, but when each contributes their best. AI expands our cognitive capacities, while human intelligence remains responsible for interpreting this knowledge through the lens of ethics, context, and accountability.
This has profound implications for leadership. Organizations that combine technological capabilities with sound judgment, effective management, and ethical leadership will thrive, not necessarily those with the most complex algorithms.
Perhaps the question should be changed. Instead of measuring AI by how much human labor it can automate, we should ask how much it can elevate human capabilities. There is a significant difference: one future replaces people, the other empowers them.
As governments, businesses, and society continue to invest in AI, equal attention must be paid to investing in human intelligence. While AI can transform the ways we work, communicate, and govern, it cannot replace the qualities that make leadership truly human. The future will be shaped not by those who create the smartest machines, but by those who continue to ask the smartest questions. This is the true promise of augmented intelligence: not that machines will one day think like humans, but that humans, supported by intelligent machines, will think better than ever before.
Leaders and specialists in corporate technology gathered at the Smarter.tech '26 event to discuss a complex question: what does it truly mean for organizations with existing complex infrastructure and overloaded teams to work more efficiently when they are now responsibly implementing AI?
The general conclusion of the event was an emphasis on context. Technology only becomes useful when it aligns with people's working environment, respects existing organizational controls, and provides teams with a practical way to operate it.
Muggi van Staden, CEO of Obsidian Systems, set the tone with his opening speech, urging participants to actively engage in the program so that everyone could gain a clearer picture of what smarter technology looks like in practice.
Van Staden noted: 'Clients are not asking for more isolated technologies. They want to know how it will fit into their environment and how it will be managed. They also need assurance that their teams can reliably manage and maintain it.'
He added that Smarter.tech '26 provided an opportunity to include these questions in one conversation with the tools and platforms shaping the market.
The Atlassian plenary session demonstrated why context has become a central element in enterprise AI. Their direction for Rovo and Teamwork Graph is based on linking organizational knowledge with the work already being done in Jira, Confluence, and other related systems, giving AI agents access to relevant information while maintaining human involvement in the process of assignment, verification, and completion of work.
Chris Mulder from Red Hat presented another aspect, describing the challenges faced by organizations that must maintain legacy workloads alongside containers and new AI platforms, often without increasing teams or budgets. His solution involved a consistent operational model built on open platforms, which ensures greater control over where workloads run and how data is used.
This idea continued in practical demonstrations conducted by Obsidian teams. One session showed how Red Hat Satellite and Ansible can replace disparate Linux server management with a managed operational model covering deployment, troubleshooting, and reporting. The importance lay not so much in the tools themselves, but in the expertise required for their integration and the discipline needed for their maintenance.
This is a familiar problem for South African organizations modernizing relatively old systems, facing skill limitations, growing security threats, and unpredictable technological costs. Simply adding a platform without first defining how it will be managed and maintained only increases complexity.
Van Staden concluded that 'smarter technology should reduce the burden on people, not give them another system to manage.' He stressed that this requires technical depth and strong partnerships underpinned by an understanding of the client's actual operational activities.
Smarter.tech '26 asserted that progress would be achieved not by chasing every new possibility, but by making better decisions about how technologies connect, who is responsible for them, and how the environment can be improved over time.
Researchers from the University of Warwick analyzed a rare episode of activity in the Swift J1727.8−1613 system and concluded that black holes are capable of ejecting a substantial amount of the matter they absorb. The work was based on observations made using the Very Large Telescope (VLT) of the European Southern Observatory.
The observations meticulously recorded a flare that occurred in 2023 when the system became one of the brightest sources of X-ray radiation in the sky. The results, published in the Monthly Notices of the Royal Astronomical Society on Thursday (the 30th), show that in addition to attracting gas from a neighboring star, the black hole also returns some of this material back into space through jets and winds, and this behavior persists even after the activity level drops to a very low level.
Black holes are traditionally described as objects that absorb everything that approaches them. However, according to the scientists, the observed behavior in the Swift J1727.8−1613 system is much more complex. The lead author of the study, Dr. Noel Castro Segura, a postdoctoral researcher at the University of Warwick, noted that the matter is captured by the system, undergoes an internal process, and a significant part of it is then ejected back. For the scientists, this indicates that these objects act more like a 'cosmic digestive system' rather than simply structures that accumulate matter.
The team used the X-Shooter instrument installed on the VLT to record one of the most detailed optical sequences obtained during such a flare. Instead of analyzing individual moments, the researchers were able to track changes in the system across various phases of activity. The system consists of a black hole that pulls gas from a nearby star, forming a disk of superheated material around itself. Since the 2023 flare was observed almost in real-time, it was possible to trace the evolution of this process with a rarely achieved level of detail. During this period, the researchers found that while the black hole emitted a powerful jet, the feeding disk was also undergoing significant changes. This relationship provides new insights into how matter falling into a black hole is connected to the material being returned to space.
The most surprising result appeared after the most intense phase of the flare ended. Even when Swift J1727.8−1613 showed only about one-hundredth of the peak activity, researchers found evidence that dense gas continued to be ejected from the system. The authors point out that this suggests that black holes can sustain intense flows of matter for much longer than previously thought. In some cases, the volume of material ejected into space may be comparable to the volume actually absorbed by the black hole itself.
According to Dr. Noel Castro Segura, this behavior could mean that black holes are less efficient at consuming matter than previously believed, as a significant portion of the captured material may never reach the object itself. Researcher Kyle Solomons, a postgraduate student at the University of Cape Town and participant in the study, emphasized that the final phase of the flare was also characterized by high activity. He noted that even when the X-ray emission dropped to a fraction of its peak value, the system still possessed enough energy to generate a large gas ejection. The authors conclude that the complete tracking of the Swift J1727.8−1613 activity cycle provides one of the most detailed pictures of how black holes capture matter, react to this process, and influence their surroundings.
Planetologists used data from the James Webb Space Telescope to determine that the chemical composition of the surfaces of Neptune's moons Proteus, Larissa, and Galatea, as well as the particles of its rings, differs significantly from the composition of other objects in the outer Solar System.
The findings best align with the hypothesis that these inner moons and rings contain material taken from the interiors of destroyed original moons or from a dwarf planet that passed by Neptune.
The nature of Neptune's ring and moon system remains a subject of scientific debate. Triton accounts for over 99% of the total mass of all moons, possessing a retrograde and highly inclined orbit relative to the planet. The remaining one percent consists of small moons, many of which also move along irregular trajectories.
There is a suggestion that Neptune initially had an ordered system of regular moons. After the capture of Triton, which arrived from the Kuiper Belt, this system may have disintegrated, and small moons and rings formed from the resulting debris. Another theory suggests that the moons and rings originated from the remnants of a dwarf planet from the Kuiper Belt that passed near Neptune and was torn apart by tidal forces.
To test these models, scientists required detailed data on the composition of the moons, but only the Voyager 2 spacecraft had previously visited near Neptune. A group of planetary scientists led by Riley Davis from the University of California, San Diego, presented the results of analyzing spectra collected by the James Webb's NIRSpec spectrograph in the near-infrared range.
The instrument recorded spectra of sunlight reflected from the particles of the rings and the surfaces of the moons Proteus, Larissa, and Galatea, which allowed for information about the mineralogical composition to be obtained. The researchers then compared this data with spectra of terrestrial meteorites, asteroids, Uranus and Saturn's moons, as well as objects in the Kuiper Belt and Neptune's Trojan 2006 RJ103.
It was found that none of the three studied moons of Neptune, nor its rings, show obvious signs of water ice, although traces of hydroxyl groups were detected. Magnesium-bearing serpentine-like phyllosilicate clays were identified on Larissa, Galatea, and in the ring particles. In the case of Proteus, such minerals are either very scarce or completely absent, but instead, signs of carbon dioxide presence were observed on both hemispheres.
For all studied objects and rings, the presence of ammonia-containing minerals cannot be ruled out. The discovery of phyllosilicate clay minerals in Neptune's rings and moons is the first of its kind among bodies outside Jupiter; typically, such minerals are found in carbonaceous chondrites and Main Belt asteroids.
It is believed that these minerals form inside parent asteroid and meteorite bodies in the presence of liquid water, at moderate temperatures (less than 300–400 Kelvin), and over a long period (more than 1–10 million years). However, the sizes of Larissa and Galatea (less than two hundred kilometers) did not allow for the creation of the necessary conditions for such reactions.
Therefore, the most probable concept is that Neptune's moons and rings consist of material from the interiors of one or more bodies that had a complex structure, including a rocky core and a mantle with ice and clay minerals. The depletion of water ice may be a consequence of the initial material being poor in volatile components, or the ice being lost subsequently.
As for Proteus, it is possible that it formed from material that never came into contact with liquid water, or it survived a collision that caused its heating and dehydration of phyllosilicates. The presence of ammonia and the abundance of phyllosilicates on Larissa and Galatea can be explained by moderate heating of the fragments (up to 700 Kelvin), indicating a relatively low impact velocity during the destruction of Neptune's original system and its subsequent evolution.
