3 strategies for using generative AI to responsibly extract data insights
Generative AI can enable us to extract the insights from otherwise unmanageable volumes of data. Image: Getty Images/iStockphoto
- Artificial intelligence (AI) has a key role to play in building high-performing, resilient and responsive enterprises in an increasingly connected world.
- However, the rapid rise in content in recent years has led to a surge of data, which generative AI (GenAI) could help us to navigate and gain insights.
- To harness GenAI effectively, organizations can follow three strategies to gain insights without exposure to the harmful consequences of unchecked AI use.
In an increasingly complex and connected world, many are keeping a keen eye on artificial intelligence (AI) to understand its role in building high-performing, resilient and responsive enterprises.
A key challenge for many organizations today is the large gap between the explosion of content we have seen in recent years and the individual who needs decision support. According to the International Data Corporation (IDC), the amount of data being created, captured, replicated and consumed will hit 175 zettabytes by next year – a nearly 300% increase compared with 2019.
Generative AI can help us navigate this data surge by making mass data quantities accessible on a human scale, enabling us to extract the insights we need from otherwise unmanageable volumes of data. However, if not used responsibly, AI can create a hall of mirrors that obscures our ability to discern truth from falsehood.
We've already seen the consequences of unregulated AI use in various arenas: the proliferation of misinformation and disinformation that affects elections, copyright violations that lead to legal disputes, and the provision of false or discriminatory legal advice that threatens the integrity of justice systems.
How to responsibly build more intelligent organizations with AI
To harness generative AI effectively and responsibly, organizations can implement the following three strategies to derive valuable insights from a sea of data, without exposing themselves or others to the harmful consequences of unchecked AI deployment.
1. Use AI for enhancing total information awareness
While knowledge is power, knowledge visibility is a superpower. For centuries, people have imagined knowledge visibility through the ability of a person to understand all human languages or even speak with animals. It is finally within our grasp to deploy such a new orchestration layer above our existing enterprise software stack.
This knowledge fabric will be agnostic to the human languages in which ideas are authored, captured, or recorded. It does not care what underlying. systems of record content reside in, and it will file type content is authored in, whether it be audio, image, text, or video.
AI is the catalyst that can finally fulfil this concept. It can tap into disparate assets – whether semi-structured, structured or unstructured – and merge them into a cohesive whole. It can be easily argued that the organizations that sit at the top of the Fortune 500, due to their economies of scale, are amongst the pinnacle brands that have been able to better predict the way the world operates because of their vanguard use of these technologies.
What happened over the last few years is a wider distribution of knowledge visibility based on lowered barriers to entry. This democratization of knowledge now enables organizations of all sizes to identify insights, patterns and trends that might otherwise remain hidden, unlocking new opportunities and exposing previously unidentified risks. This empowers leaders with decision advantage, delivering the information they need to act in a fast-paced world.
2. Curate a collection of content that you can rely on
With the influx of unchecked generative content, the internet can become a hall of mirrors where we will not know what is real and what is not. So how do we safeguard our intelligence?
To overcome uncertainties, organizations need to create their own knowledge fabrics for their value chains. This construct serves as a repository of reliable information, ensuring you always have attributable, trustworthy, and verifiable content you can rely on. This could include:
- Proprietary content that makes up your unique intellectual property
- Published content that is properly licensed and provisioned for your use
- Public information from government agencies that regulate your industries
- Private information that is unique to you as an individual
We have the opportunity to enter a new era of information discovery where we can fall back to trusted sources and put up guardrails to protect our data from disinformation and unreliable input.
3. Grow usage while maintaining control over your technology
Not all content is created equal, and the same is certainly true for AI tools. To get started with a responsible AI framework, you need to identify how much control you will have over your content and your AI model and then scale your usage accordingly.
To do this, you can use a simple matrix that represents control over your content on one axis and control over your AI technology on the other, as outlined with possible actions to take below.
Strong control over content and AI
- Example: Extractive AI technology, which pulls information exclusively from approved sources and delivers it verbatim with clear attribution.
- Recommended AI use: Use the output directly.
Strong control over content and moderate control over AI
- Example: Retrieval-augmented generative (RAG) tools, which retrieve information solely from approved sources while introducing a generative layer.
- Recommended AI use: Use the output directly. Set guidelines to ensure users engage responsibly.
Weak control over content and AI
- Example: Ungrounded generative AI solutions, which can pull information from biased, copyrighted, inaccurate, or even malicious content.
- Recommended AI use: Tread lightly and carefully review output.
Advancements in cognitive computing have made knowledge fabrics a reality, offering unprecedented levels of accuracy, scale, security and speed. By selecting high-value information retrieval use cases, curating trusted content collections and understanding the technologies’ control planes, even the most sensitive workflows can finally be addressed.
How is the World Economic Forum creating guardrails for Artificial Intelligence?
Amidst the current data deluge, AI presents a transformative opportunity to build more intelligent organizations by reducing the distance between knowledge and people. If Steve Jobs considered the personal computer the bicycle for the mind, then AI – as another landmark in technological development – becomes the rocket ship for it.
With the proper AI safeguards in place, organizations can make more informed decisions, navigate new challenges in a dynamic world, and shape a more sustainable future for all of us.
Don't miss any update on this topic
Create a free account and access your personalized content collection with our latest publications and analyses.
License and Republishing
World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.
The views expressed in this article are those of the author alone and not the World Economic Forum.
Stay up to date:
Artificial Intelligence
The Agenda Weekly
A weekly update of the most important issues driving the global agenda
You can unsubscribe at any time using the link in our emails. For more details, review our privacy policy.
More on Emerging TechnologiesSee all
Devanand Ramiah
December 6, 2024