The basic question we need to address is, “Do we in business need to get involved in AI?”
Of course, the answer is: YES. If we don’t get involved, our competitors will be happy and leave us behind.
The next question is, “Do we focus just on general AI or move into generative AI?”
The answer is: we need to engage in both. Generative AI and general AI represent different aspects of artificial intelligence.
Generative AI focuses on creating new content or ideas based on existing data. It has specific applications and is a subset of AI that excels at solving particular tasks.
General AI, also known as artificial general intelligence, broadly refers to the concept of AI systems that possess human-like intelligence.
General AI is still the stuff of science fiction; it represents an imagined future stage of AI development in which computers are able to think, reason, and act autonomously.
Find out what industry observers have to say about “Unlocking the power of generative AI and navigating AI governance”.
It depends on who you ask, but many experts believe that generative AI has a significant role to play in the future of various industries.
The capabilities of generative AI have already proven valuable in areas like content creation, software development and health care, and as the technology continues to evolve, so too will its applications and use cases.
Other uses of generative AI include:
Healthcare: Generative AI is used in medicine to accelerate the discovery of novel drugs, saving time and money in research.
Marketing: Advertisers use generative AI to craft personalised campaigns and adapt content to consumers’ preferences.
Education: Some educators use generative AI models to develop customised learning materials and assessments that cater to students’ individual learning styles.
Finance: Financial analysts use generative AI to examine market patterns and predict stock market trends.
Environment: Climate scientists employ generative AI models to predict weather patterns and simulate the effects of climate change.
That said, the future of generative AI is inextricably tied to addressing the potential risks it presents. Ensuring AI is used ethically by minimising biases, enhancing transparency and accountability and upholding data governance will be critical as the technology progresses.
At the same time, striking a balance between automation and human involvement will be crucial for maximising the benefits of generative AI while mitigating any potential negative consequences on the workforce.
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It’s important to note that generative AI presents numerous issues requiring attention. One major concern is its potential for spreading misinformation or malicious or sensitive content, which could cause profound damage to people and businesses – and potentially pose a threat to national security.
These risks have not escaped policymakers. In April 2023, the European Union proposed new copyright rules for generative AI that would require companies to disclose any copyrighted material used to develop these tools.
Hopes are that such rules will encourage transparency and ethics in AI development, while minimising any misuse or infringement of intellectual property. This should also offer some protection to content creators whose work may be unwittingly mimicked or plagiarised by generative AI tools.
In a draft document, the EU is considering tougher cybersecurity regulations including forcing non-EU cloud service providers to only handle sensitive data through a joint venture with an EU-based company. The document would also require the cloud service to be operated and maintained from the EU.
There is no doubt that AI will change the world, whether we like it or not. It is trusted that we will have a happy union of people and machines.
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Contributed by: Henry J. Schumacher (schumacher@eitsc.com), President of the European Innovation, Technology and Science Center Foundation (EITSC).
This article was first published in BusinessMirror on 16 May 2023.
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