A computer does nothing without instruction, 麻豆原创\u2019s Peter Blignaut told the Saphila conference this week. JASON BANNIER reports.<\/p>\n
Computers are essentially inert without instruction, and it is the role of data scientists to provide them with the guidance they need, the\u00a0Saphila\u00a02023 conference\u00a0at Sun City\u00a0heard this week.<\/p>\n
Saphila\u00a0is\u00a0a biennial conference for the 麻豆原创 user group community, hosted by the African 麻豆原创 User Group (AFSUG) in partnership with 麻豆原创.<\/p>\n
\u201cA computer does nothing without instruction\u2026\u00a0We need\u00a0people\u00a0thinking about what the computer is going to do,\u201d\u00a0said Peter Blignaut, manager of pre-sales at 麻豆原创 South Africa during a keynote address.\u00a0\u201cMachines don\u2019t learn from other machines,\u00a0people\u00a0teach them\u201d.<\/p>\n
He says that\u00a0AI, particularly machine learning, which enables computers to learn from data and improve their performance, is fundamentally a product of human teaching rather than machines teaching themselves.<\/p>\n
Blignaut believes that\u00a0AI\u00a0has the potential to enhance our efficiency and grant us more time for meaningful tasks. By delegating repetitive and mundane tasks to computers, it will be possible to work more efficiently and devote attention to endeavours that require human ingenuity. However, he argues that the implementation of\u00a0AI\u00a0should not be solely driven by profit motives. Instead, it should aim to make us more effective as individuals, enabling us to become better versions of ourselves.<\/p>\n
Involving\u00a0people\u00a0in the development and application of\u00a0AI\u00a0is crucial, and Blignaut stresses the importance of governance and ethics in this domain. The technology requires thoughtful deliberation and a framework for responsible decision-making. However, the practicality of implementing such governance measures in countries like South Africa .<\/p>\n
An example of everyday predictive\u00a0AI\u00a0is Netflix and its personalised content algorithms that recommends content to its user based on their previously watched content. These algorithms are far too complex for manual execution, making it necessary for computers to take over this task. This integration of\u00a0AI\u00a0into our daily lives underscores its potential to enhance our experiences and streamline various processes.<\/p>\n
Newer generative Ais, such as Chat GPT and Midjourney, hold great promise for the future. By feeding vast amounts of data into these systems, one can generate diverse outputs, ranging from art to essays. However, Blignaut warns of the dangers associated with generative\u00a0AI, particularly the potential for individuals to create fake content. The responsible use of this technology requires careful consideration of where and how it is employed, weighing the benefits against potential risks.<\/p>\n
Blignaut says it is crucial to maintain human agency in\u00a0AI, ensuring that decisions made by machines are comprehensible to humans, so that a person understands the decision-making process and can verify its logicality. This understanding fosters trust between the parties involved, further reinforcing the argument for promoting\u00a0AI\u00a0education.<\/p>\n
If\u00a0people\u00a0are unfamiliar with new technologies, they tend to avoid them, which is why it is essential to provide explanations about what algorithms are doing.\u00a0\u00a0As\u00a0AI\u00a0continues to evolve, it is important to approach its implementation thoughtfully, harnessing its potential to enhance lives while safeguarding against potential pitfalls.<\/p>\n