Latest news with #MachineIntelligence
News24
4 days ago
- News24
Human, beware? Arthur Goldstuck delves into the rise of AI
News24's Book of the Month for August, The Hitchhiker's Guide to AI: The African Edge, reframes the conversation about AI through the lens of human roles and merges global advances with distinctly African realities. From farmers using AI to track bee movements, to school pupils guided by WhatsApp tutors, to musicians experimenting with machine-made beats, this book explores how everyday people across the African continent are shaping – and being shaped by – the rise of machine intelligence. Rather than obsessing over distant futures or Silicon Valley breakthroughs, this book brings AI down to earth. Through the eyes of local and international teachers, coders, executives and artists, it tells the story of Africa's AI moment – not as a catch-up game, but as reframing the global narrative. Arthur Goldstuck is the author of 21 books and the founder of World Wide Worx, Africa's leading technology market research organisation. This is his second book on AI. In this excerpt, he writes about how AI learns to interact with humans. Natural language processing Chatted with any interesting computers lately? Your knee-jerk reaction is probably that you don't talk to machines, but you are also probably deluding yourself. For example, most people nowadays find that the easiest way to get account statements, if the option if offered by your institution, is to call up a menu on WhatsApp and follow a sequence of instructions. Sometimes, instead of a number from a menu, you are asked to type in what you want. Miraculously, maybe, the machine gives you what you want. Many companies, ranging from Discovery Health to Mercedes-Benz to MTN to Vodacom, are using more advanced chatbots to do the same thing. The results tend to be disappointing, as most of the chatbots are designed merely to pull answers from an existing menu on a standard website. But they are getting better all the time. More and more of us are succumbing to the lure of voice assistants on our phones and smart speakers, asking Siri (Apple), Google Assistant or Gemini (Android), Celia (Huawei) or Alexa (Amazon) for directions or to play a song. Again, the machine obeys. Unless you are in a car and talking to the clunky built-in voice command system, in which case the machine almost always gets it wrong. But connect Google Android Auto or Apple Car Play to the car, with their access to the latest voice technology, and it is suddenly obeying your spoken commands. How? Thanks to natural language processing (NLP), a system for programming computers to process and generate text, speech and other forms of human language. The idea is to teach computers to understand and communicate with humans using the language we speak or write. In short, it's all about bridging the gap between human language and computer language. But how? It starts with data. Vast amounts of it. Computers are fed with text from numerous sources and programmed to analyse and study the text to learn patterns, grammar and meanings behind words and sentences. Once it has passed English – or any other language – in this school, it is ready for any form of language processing. NLP can automatically summarise a long article into a short paragraph, translate sentences into other languages and analyse the sentiment in social media posts. ChatGPT told me that sentiment analysis is 'like the computer reading your mind', but that's just wishful thinking. It merely matches a large dictionary of attitude-related words to a set of rules that indicates whether a word is positive, negative or neutral. When it works, it helps businesses gather insights about how people feel about their products or services. But think of a young person describing something as 'sick' or 'wicked'. If the system is not programmed to pick up on slang, it will interpret a great positive as a negative. Once again, it is a case of: human, beware. NLP algorithms use various forms of artificial intelligence, including machine learning, to break down sentences, look for keywords and analyse the context to generate meaningful responses. As the algorithms improve, and computing power improves, NLP improves. Before long, the science-fiction-like promise of instant and automatic translation of languages for travellers will be an everyday reality. With luck, but don't hold your breath, large companies' customer services will be transformed. Intelligent automation Intelligent automation combines the power of automation and AI, with a promise of bringing efficiency, accuracy and intelligent decision-making to business processes. Left to itself, this form of AI has the power to wreak havoc, so let's first look at the nightmare before we address the dream. On 6 May 2010, long before AI had entered common use in business, Wall Street was rocked by an event known as the 'flash crash'. A combination of market conditions and high-frequency trading algorithms, designed to execute trades at extremely fast speeds, resulted in a flood of automated sell orders that led to a cascading effect and a sharp fall in prices. Because there was an insufficient number of buyers to counter the selling, some stocks briefly traded at absurdly low prices, as low as a cent or a fraction of a cent. Aside from widespread panic, it result ed in the temporary loss of billions of dollars – before the market rebounded just minutes later. ChatGPT tells us: 'The incident underscored the importance of monitoring and managing the risks associated with automated trad ing algorithms. It highlighted the need for robust risk management mechanisms, circuit breakers, and coordination between market participants and regulators to ensure market stability in the face of rapid algorithmic trading.' Now that you've been warned, you probably won't rush into intelligent automation, but let's pause and take a breath. At its core, intelligent automation automates repetitive and rule based tasks that were traditionally done by humans. This means it can streamline routine operations, save time, and reduce errors in data entry, invoice processing or report generation, for example. It is one of the categories of greatest impact of AI on business, not only because of what it can do, but what it allows business decision makers to do: free up their time for more strategic and value-added activities. The key is in that word that is at the heart of this book: 'intelligence'. With AI added on, machines go beyond simple automation to analyse vast amounts of data, recognise patterns and, ultimately, make decisions. Intelligent automation plays a crucial role in fraud detection, risk assessment and financial analysis, making it a powerful tool for financial services organisations. It is at the heart of a new generation of insurance companies, like South Africa's Naked, which uses AI at every stage of the customer journey, from getting a quote and signing on to making a claim. But the possibilities go far beyond moving money. The ability to process large volumes of data quickly, and identify anomalies, predict trends and make informed recommendations, offers efficiency and minimises risk to any business that produces a large amount of data. By leveraging AI algorithms, machines can analyse data from multiple sources and provide insights for strategic planning, market analysis and forecasting. The integration of automation and intelligence in business processes can also allow collaboration between machines and humans. This means it enables businesses to improve productivity and allocate human talent to more creative and critical tasks that still require people's touch and expertise. Behind the scenes, intelligent automation feasts at a smorgasbord of AI tools, including machine learning, natural language processing and computer vision. That makes for better results over time. As these improvements multiply, they can have the very opposite effect of the likes of a flash crash. They promise a boost in value that is sustainable, measurable and, for the humans who keep their jobs, deeply satisfying.
Forbes
24-07-2025
- Business
- Forbes
Will Superintelligence Save Us—Or Leave Us Behind
Srinivasa Rao Bittla is an AI-driven performance and quality engineering leader at Adobe. What happens when machines begin to think for themselves? Artificial Superintelligence (ASI) represents not just a potential technological leap but a possible defining moment in human history. A more potent frontier is emerging as AI transforms industries and redefines possibility: machine intelligence that could one day surpass human capability in nearly every domain. While current systems remain far from this capability, the prospect of ASI is the subject of growing research and debate. Understanding ASI: Beyond Narrow AI Today's large language models operate within limited, task-specific boundaries. Though they learn from vast datasets and automate complex tasks, they remain tools, constrained by human design and lacking true understanding, consciousness and independent intelligence in any human sense. By contrast, ASI would exceed human ability not just in logic and memory, but in creativity, emotional insight, strategic reasoning, and adaptation. It could set its own goals, draw from multiple disciplines and generate solutions beyond even our most gifted thinkers. However, no existing system today demonstrates these capabilities, and expert opinion varies widely on when—or even if—they will emerge. The Road To Superintelligence: Evolution Or Explosion? Some researchers envision a gradual evolution, as neural networks improve and compute power increases. Others warn of a tipping point—often referred to as the singularity—where machines begin to improve themselves, rapidly escaping human control. Signs of this shift are emerging. From generative AI to reinforcement learning to neuromorphic hardware, advances from labs like OpenAI, DeepMind and open-source communities are making incremental advances in narrow AI capabilities, not demonstrations of self-improving general intelligence. Economic Impacts: Promise And Precarity ASI could usher in a new era of economic growth. Scientific breakthroughs, sustainable infrastructure and advanced life-saving therapies may arrive at speeds no human can match. Productivity could soar. Entire sectors—from energy to education—may be reimagined. Imagine ASI crafting climate adaptation strategies in real time or engineering atomic-scale materials for sustainable energy storage. Its impact could eclipse that of the digital age or the Industrial Revolution combined. But disruption is inevitable. Even roles once considered safe—creative leadership, legal analysis and strategic planning—may be vulnerable. If machines outperform us in judgment, empathy and innovation, what is left for humanity? These shifts raise urgent questions about inequality, economic distribution and value alignment. Would ASI deliver abundance or deepen the divides between those it empowers and those it displaces? Existential Risk Or Civilizational Leap? ASI could also bring profound risks. Thinkers such as Stephen Hawking, Elon Musk and Nick Bostrom have warned about the potential misalignment between ASI goals and human values. A system tasked with maximizing an unclear objective could behave in ways that are harmful to people and the planet. This possibility of ASI is no longer dismissed as science fiction—its implications are now taken seriously by leading institutions. Still, ASI itself remains hypothetical. An ASI with access to infrastructure and the ability to self-improve could pursue goals that violate ecological, ethical or human survival boundaries. While these scenarios remain hypothetical, their scale and potential impact have prompted serious attention from researchers and policymakers. That is why alignment—the field ensuring AI systems serve human interests—is one of the most urgent challenges in tech today. Many consider alignment to be a key long-term priority, though others argue that immediate issues like algorithmic bias or misuse of narrow AI remain more pressing in the short term. Yet policy, research and safeguards still lag behind. Governments will need to regulate ASI proactively, much as they do with nuclear power or gene editing. Toward Human-Machine Symbiosis Some experts envision ASI not as a threat but as a collaborator—a cognitive partner. Integration, not domination, could define the future. Brain-computer interfaces, such as those under development at Neuralink and academic research groups, hint at real-time human-ASI cooperation. This doesn't mean our creativity or compassion will be erased. It may reveal how central those traits truly are. Still, caution is essential. As mind and machine converge, questions about mental privacy, cognitive autonomy and ethical manipulation become pressing. Who Governs Superintelligence? Perhaps the most urgent question is governance. Who would control ASI? Would it rest with a few multinational tech giants, authoritarian states or a democratic, decentralized coalition of global stakeholders? Without transparency and regulation, ASI could concentrate power in ways far more dangerous than nuclear capability. Monopoly over intelligence could redraw geopolitics. A global pact—akin to the Treaty on the Non-Proliferation of Nuclear Weapons—may be required. It should define ethics, oversight mechanisms, safety thresholds and accountability. What Should Leaders And Innovators Do Now? While ASI may still be decades away, early preparation and risk awareness are critical. Leaders can take several immediate steps to prepare: • Invest In Ethics And Alignment: Build teams focused on long-term risks and socially responsible development. • Promote Transparency: Opaque systems are untrustworthy. Encourage interpretability and explainability. • Support Open Collaboration: Share breakthroughs responsibly through open scientific channels. Closed innovation magnifies ASI risks. • Get The Workforce Ready: Train for human skills machines can't replicate—empathy, creativity and critical thinking. • Participate In Global Policy: Take part in cross-border dialogues on data governance, safety standards and ethics. Conclusion: The Choice Is Still Ours ASI is a test of our morality, foresight and imagination. Whether it becomes humanity's greatest tool—or our greatest threat—depends on choices made now. Although ASI remains speculative, its potential impact demands careful planning and preparation. We must be bold, thoughtful and humble—carefully preparing for the possibility of its emergence within our lifetimes. The real question is not whether machines will think, but whether we will think wisely enough before they do. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
CTV News
20-05-2025
- Science
- CTV News
AI industry leaders in Edmonton for Upper Bound conference
Student researchers work at the Alberta Machine Intelligence Institute in downtown Edmonton (CTV News Edmonton/Matt Marshall).
