The evolution of artificial intelligence has been so swift and steady that it no longer feels too futuristic. We are at the dawn of a new era, where newer capabilities and potentials in machines are being unlocked every day. What appears too far-fetched or imaginative tends to become a reality in a short period.
Remember the time we talked about chatbots as a trend a couple of years back? Today, we have them resolving most of our queries and complaints with minimal to zero human intervention. Over the last few years, NLP has evolved, computer vision has become more pervasive, AI-based anomaly detection in cybersecurity has amped up, and more.
While these continue to evolve, we have newer wings and niche branches cropping up in AI. Let’s look at what trends will lead the way forward for AI in 2023.
3 Trends in AI To Look Out For In 2023
AI Democratization
When we talk about AI, the scenarios we mostly relate to are industrial automation, robotic arms, RPAs, and more. There is a minimal personal level connection in experiencing AI apart from the features and modules on our smartphones, televisions, and consumer gadgets.
In the coming months, however, we will witness the democratization of AI, where people with no specialization or even exposure to AI can work on it seamlessly. This will be similar to the no-code revolution that allowed small business owners with no technical expertise to set up a website from scratch for their shops. The technology will reach places and people who have their super-specific requirements and concerns to resolve using AI.
Creative AI
For a long time, we’ve been having a debate on whether AI would take up our jobs. A lot of us also believed AI would never influence a field such as the arts, where creativity, human imagination, and interpretations are key.
But this is changing fast. Generative or Creative AI is increasing and is both interesting and scary at the same time. There are applications from OpenAI called GPT3 (and the upcoming GPT4), which are opening unimaginable potential in creating works of art. They can write an entire movie script from scratch just through prompts.
Besides, some apps produce original digital artworks in seconds, customized to specific requirements like renaissance style, Van Gogh style, acrylic, and more. There’s one AI-based music generator tool for artists as well. All it takes is some instructions through random text-based prompts.
And we’re not even getting to the Deepfake and de-aging capabilities of AI.
Ethical AI
AI, for now, is unaccountable. There is a blind implementation of AI and interpretations of its output. Right now, there are just outcomes. But how good are they? Let’s do one better. How fair are they?
Ethical AI will lay the foundation for fair, bias-free, and responsible processing of data for airtight outcomes. This is crucial for enterprises that process massive volumes of data and have complex AI systems working for both customer and internal workflows and outcomes. Unfair results could not just lead to a bad reputation but lawsuits as well.
While we’re here, aspects like Explainable AI will simultaneously continue to rise in the coming months. This will complement the ethical aspect of its functioning, where AI will be held accountable for its decisions and outcomes. AI will be required to justify an output through fair and objective reasoning.
Final Thoughts
We’ve come a long way from the time we all said that AI was the future. This is the future we talked about, and the impending timeline appears more exciting than ever, with limitless possibilities.
While we continue to push barriers in the coming decade, the upcoming year will have AI specialists and tech enthusiasts work towards laying the strongest and the fairest foundations for AI processing and implementation. These four aspects we discussed are examples of that.
Written by Siddharth Pant, Head of Data Sciences (Academics & Operations), UNext Learning
thanks a lot and keep up the good work.