Intelligence-On-Tap: ChatGPT’s Promise

In recent years, we have prioritised equitable AI use. The Slalom Ventures accelerator programme, a global initiative supporting impact-focused tech companies, is currently supporting two UK-based startups, PSI and Point Sigma. These startups employ AI tools to enhance the accessibility of focus groups and data analysis.

Another distinctive aspect of the latest AI transition to image/video generation is accelerating pace of evolution in these tools and making it increasingly challenging to keep up with. Tools like AutoGPT enable large language models to prompt themselves and boot up specialised AI agents that can perform various tasks, such as data analysis, statistical model creation, and web browsing. Although implementations are often crude today, the pace of development in this field is relentless. The idea of deploying multiple intelligences simultaneously to coordinate and accomplish a goal - from strategy to plan, projects, tasks, and back to checking goal completion - signifies a new era. Adapting to the concept of intelligence that can be turned on like water from a tap will require radical adjustments.

For these models to achieve widespread adoption, transparency is crucial. Users will need to build their trust in the answers provided by AI and comprehend the steps taken to reach those conclusions. Promising solutions to improve transparency are evident in recent collaborations, such as the one between OpenAI and Wolfram. Wolfram Language, known for its deep logic and mathematical capabilities, has been integrated to ChatGPT as a plugin that enhances problem-solving abilities while detailing the steps taken to arrive at an output.

All organisations need to be thinking of and prioritising the most valuable use cases and impending risks for use of AI. Ensuring they integrate new technologies into their workflows thoughtfully for the benefits of employees, customers, and investors.

The era of intelligence-on-tap is upon us. With the promise of large language models like ChatGPT comes significant potential to build better tomorrows for all. But this potential will not be fulfilled without hard and focused work to ensure risks are mitigated. We must step-up our vigilance on risks and biases these new technologies will bring, and focus on transparency, fairness, and inclusivity, to ensure that the benefits of large language models are shared equitably, rather than exacerbating existing disparities between the most and least privileged.