Balancing risk and reward: how to responsibly use generative AI for business

Balancing risk and reward: how to responsibly use generative AI for business

Generative artificial intelligence (AI) can produce text, images, or other content in response to prompts. It has the potential to streamline workflows in virtually every sector, from education and manufacturing to banking and life sciences.

In fact, Australia’s Generative AI Opportunity?report predicts this technology could contribute $115 billion annually to Australia’s economy by 2030.

Its ability to generate a multitude of possibilities instantaneously can empower humans to explore new and novel concepts that might otherwise remain undiscovered. For small businesses and sole traders, generative AI can scale operations at speed, transforming time-intensive tasks into quick and efficient processes.

But all of this is only possible if it’s implemented responsibly.

Australia’s Responsible AI Network?(RAIN) is a world-first program bringing together experts, regulatory bodies, practitioners and training organisations to empower Australian businesses and industries to responsibly adopt AI technology.

RAIN's?interactive and free workshops are run by AI experts that explain and demonstrate the methods, tools and practices needed to responsibly use AI.

Here, we recap the highlights from our recent workshop on generative AI, starting with the fundamentals of the technology –?Large Language Models (LLMs).

What are Large Language Models (LLMs)?

LLMs are a form of AI that recognise, translate, summarise, predict, and generate text.

They form the algorithmic core of text-based generative AI, like ChatGPT. They’re designed to use and understand language in a human-like way.

You’ve experienced earlier versions of this technology in automated text prompts while messaging on your smart phone, or ‘quick response’ suggestions when emailing.

This kind of response prediction and answer generation technology now underpins a variety of sophisticated tools. These include virtual assistants, market research analysis, fraud detection, cybersecurity programs, and medical diagnosis technology.

How do they work?

LLMs are trained using vast amounts of data, which is partly where the ‘large’ in large language model comes from.

It would take a human 2,000 years to read ChatGPT3’s training data. Generally, the more data the LLM is trained on, the more capable it is at using and understanding language.

The current generation of LLMs are pre-trained on billions of words of text from sources such as books, websites, academic papers and programming code.

From a 'base model', LLMs can be customised with a much smaller amount of industry-specific information. This approach is both more practical and more affordable than attempting to build one from scratch.

What can generative AI help with now?

  • Writing emails: Writing a tough email that needs to make a strong point while preserving the relationship can be time consuming. Generative AI can help by assessing the tone and making it more diplomatic or assertive.
  • Market research and analysing trends: Using generative AI to constantly scan the horizon and identify industry trends is a significant time saver. That half a day of researching or conducting market analysis can be replaced by some well-worded prompts on ChatGPT.

  • Creating content:?Talk Agency are using generative AI to produce blogs, email marketing and social media copy for clients. According to the director, their writers have turned a five-hour job into a three hour one. But beware of hallucinating AI – where the system confidently provides incorrect information. This is a risk that needs to be managed by a human fact checker.
  • Building websites: Creating a website can now be as simple as entering a description of what you want and answering some follow up questions. There’s no need for technical skills or hours spent perfecting the design and functionality.
  • Chatbots:?Damien McEvoy Plumbing is using generative AI chatbots to improve the quality of customer service. “These chatbots can comprehend customer inquiries, provide accurate information and offer personalised recommendations,” he told the Prospa blog. Bear in mind customer expectations are increasing on par with chatbot popularity, with systems requiring sophisticated conversational capabilities.

According to Google’s Scott Riddle , they’ve been overwhelmed by the interest in generative AI from Australian businesses big and small.

Canva is using Google’s generative AI translation services to better support its non-English speakers and is exploring ways that Google’s LLM technology can turn short video clips into longer, more compelling stories.

“We’re starting to see a real groundswell of generative AI activity in the local startup community too. Rowy, an exciting Sydney based low/no code platform startup, has been a great earlier adopter of our generative AI technologies,” Scott said.?

To continue reading about:

  • The risks of LLMs and how to mitigate and manage them, with thought leadership from Gradient Institute 's Dr Lachlan McCalman .
  • The benefits of LLM-powered generative AI with insights from Responsible AI Think Tank leader and former Australian Red Cross CEO Judy Slatyer .
  • How to responsibly use generative AI in a business setting, with commentary from Judy Slatyer and 谷歌 Partnerships Manager (Australia and New Zealand) Scott Riddle .
  • What the future holds for generative AI use.

Continue reading here.



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