AI For One and All

The Flavors of AI democracy

AI is not only for engineers and data scientists but also for managers, VPs and CXOs to leverage themselves and ensure usage of AI across their organization in bringing productivity and cost benefits. True democratization of AI is in enabling functions (HR, finance, operations, legal) across the organization to leverage its full potential in everyday work-life while making it simplified and amplified. It should also simplify the end customers routines and interactions with the company.

Read: Role of AI in Cybersecurity: Protecting Digital Assets From Cybercrime

A host of AI tools like ChatGPT, Midjourney, Gemini, Bedrock, Grammarly, Bing Search, etc are already used by masses. But there is more than one way to define the democratization of AI.

For London-based Stability AI, democratizing AI means opening up access to AI design and development to a larger community of users. This company open sourced its deep learning, text-to-image model to empower developers around the world to use, modify and innovate with the tool, subject to terms of use. The idea being that allowing developers closest to the end-users free access would produce the best outcomes, and evolve the model itself over time.

A more common way of democratizing AI development is allowing even non-technical users with little programming knowledge in an enterprise to build and modify models to suit their requirements with the help of low-code and no-code tools.

Less known but critical nonetheless is the democratization of AI governance. This is not about allowing anyone to use, monitor, and control AI as they please; rather it is about preventing the monopolization of AI by a few entities by allowing the interest and participation of a large number of stakeholders to influence decisions on how the technology should be used and by whom, within risk versus reward guardrails.

In the traditional environment, access to the data sandbox and the ability to utilize the data within it might be limited to a select group of technical specialists. Limiting access to data sandboxes hinders innovation in several ways in the AI era. A successful culture of experimentation is an ongoing process that requires continuous effort and commitment from everyone involved, not just the technical specialists. Democratizing access to data within sandboxes empowers business users with access to data in the sandbox. They can experiment with user-friendly AI tools and pre-trained models to automate tasks, identify patterns, and gain insights relevant to their roles. This enables them to leverage the power of AI without needing advanced technical expertise.

At times, democratization of AI development can clash with democratization of governance – for example, when developers are restricted from using data that is valuable for innovation but is protected by regulation. But eventually, all democratization efforts are directed at putting the power of AI within reach of every individual. About sharing the benefits of AI technologies throughout the organization. About making it possible for business users to create the use-cases best suited to their needs without depending on IT or undergoing extensive technical training.

In theory, at least. But execution is a little more complicated.

AI pays, but also punishes

Democratization leads to scale, and potentially, unprecedented benefits, but handled badly, it is a recipe for unmitigated disaster. Imagine a large community of developers around the world using an algorithm with biased training data to build other AI models; they will have magnified and perpetuated its discriminatory outcomes in next to no time. In democratized AI enterprises, marketers tap AI platforms and their customer data to identify leads, insurers study health information to price premiums, and relationship managers access customers’ financial statements to personalize investment portfolios. Without robust security measures – about access rights, permitted devices, consent – and sensitization to responsible use of AI and data, there is a real risk of the systems being breached by malicious actors, or information of a private or sensitive nature being leaked out of the organization. From financial and reputational loss to disruption of systems, to legal repercussions, uncontrolled, ungoverned, democratization can lead to very serious consequences.

Read: AI in Content Creation: Top 25 AI Tools

Proceed with care

Which is why data and AI must be democratized the right way.

The first step is to understand how different users will engage with AI (use to query or to create content, use insights to make decisions, modify or develop models, etc.) Upskilling all users including non-technical business users ensures safe and effective use of AI. Before allowing employees free rein, employers should also provide guidance on responsible AI practices, such as how to avoid subjectiveness and bias while assigning data labels. Solutions like smart data fingerprinting uncovers more data with transparency and traceability, providing a foundation for experimentation for any AI or GenAI project. Easy access to diverse datasets opens doors for “responsible data sandboxes” for creative exploration to drive organizational growth. It also promotes data sharing and facilitates seamless data exchange between different systems including AI/ML applications. Organizations may want to consider using technology infrastructure, such as MLOps, to support AI training and deployment.

As more users work with and on AI, they expose the organization to greater cybersecurity risks; secure coding practices, rigorous testing, and responsible data handling will mitigate vulnerability to attack and prevent misuse of data.

Introducing fairness and accountability checks during development will lower the probability of biased or inaccurate algorithmic outcomes and inspire trust in the applications. Building transparent and explainable AI models is key. While allowing more people to participate in designing and building AI models, enterprises should appoint a qualified human in the loop for overseeing responsible development. But even a “fair” algorithm can produce unfair outcomes if trained on flawed data: think of a dataset of potential borrowers that excludes ethnic minorities; an AI loan approval system using this data may end up rejecting eligible borrowers from those communities.

While democratization of AI will help the majority of employees become more productive and creative, it could displace some workers; employers must reskill and upskill these people for redeployment in other roles.

Share the benefits

Democratizing AI is not just about giving access to the latest tools, but it is about empowering employees at all levels to make better data driven decisions using AI, innovate by collaborating with AI, reduce biases, and deliver tangible results with improved productivity and efficiency. It allows every individual in the organization, regardless of rank or function, a share in this revolutionary technology creates inclusion, improves morale, and elevates employee experience.

These benefits directly translate into tangible and intangible business value like increased sales, customer satisfaction, and brand reputation.

By democratizing AI, companies can bridge the gap between execution and value. Ultimately, businesses can create strategic advantage to the stakeholders and achieve long term sustainable success.

Employees in every role can use generative AI to create a variety of content – text, visual, audio, code – and to produce new and innovative ideas. For example, instead of deferring to brand custodians, marketing staff can use pre-trained gen AI tools to independently build “creatives” in conformance with brand guidelines, including color, font, and tone of voice. A product development team can input desired parameters into the tool and instruct it to create multiple design options, to save substantial costs and time.

Helping everyone feel empowered and happy at work. What is democracy, if not this?

Read: AI In Marketing: Why GenAI Should Be in All 2024 Marketing Plans?