As artificial intelligence tech becomes more widely adopted by businesses–integrated in everything from chatbots to threat detection (and so much more), it’s hard not to wonder “What’s next?” Members of CompTIA’s AI Advisory Council provided some enlightening and eye-opening answers to that question for 2022. As artificial intelligence technology becomes more widely adopted by businesses–integrated in everything from chatbots to threat detection (and so much more), it’s hard not to wonder “what’s next?” We posed that question to members of CompTIA’s AI Advisory Council and received some enlightening and eye-opening responses. Here are the predictions of AI leaders for 2022. These predictions are the opinions of individual members of the AI Advisory Council and do not reflect the views of the AI Advisory Council or their respective employers.
AI Initiatives will be more fair and transparent if there is a greater awareness of this.
“We expect organizations adopt an AI-first approach for platforms, processes, and digital transformation. With embedded AI at the heart of operations optimization, we expect them to do so. Responsible and trustworthy AI will also grow significantly over the next year. This will be driven by organizations in regulated sectors driving fairness, transparency, and persistent initiatives within their AI systems.” – Mechie Nakengla, CEO, Data Products LLC
Consumers are at the center of Recommendation Engines
“ML-powered recommendation engines are going to play an increasing role in consumer technology as behavioral information is leveraged to minimize decision fatigue, optimize user experiences, and optimize user experience.” – Lloyd Danzig (chairman and founder of International Consortium for the Ethical Development of Artificial Intelligence)
More accessible and better language models
“This year, large language model (foundation models) will be more easily accessible through SaaS or APIs. They are commonly used in enterprise applications such as chatbots and translations. Open-source research will help enterprises build better services even as the models grow in size, from billions to trillions of parameters.
Multimodal Architectures Integrating Video, Audio, Text
“I look forward to multimodal AI architectures that integrate video, audio, text. These multimodal models will be embedded in many real-world applications, apart from marketing and digital art, as we see them.” – Uday Tatiraju vice chair, CompTIA AI Advisory Council
Robots to help with household chores
“We will see more robots entering the real world to assist us with chores such as cleaning and cooking. Robots can learn multiple tasks with the help of reinforcement learning and deep learning. “We also need better laws and regulations to help those who may lose their jobs to robots,” – Uday Tatiraju vice chair, CompTIA AI Advisory Council
AI-Infused Apps Will Be More Transparent and Explainable
“As AI-infused solutions become more widespread, trust will be a top-class requirement in all AI-infused applications. Users cannot use something that isn’t transparent and not explicable.” – Rama Akkiraju IBM Fellow
App Growth Will be Propelled by the maturity of AI Platforms
“Just as Web servers needed to be mature in order for web services to take flight, AI platform maturity is an important criterion to ensure that AI-infused applications grow. I believe we will see more maturity in both the open-source platform and vendor-built platforms for AI platforms. “In addition, there will be more applications for delivering insights at edge devices. It will be possible to combine cloud, machine learning, data at the edge via data fabrics and internet of things devices (IoT), in the future.” – Rama Akkiraju – IBM Fellow
Deep Fakes and Deep Fake Detectors
“Generative Adversarial Networks, (GANs), will continue to power fakes of everything (news videos, documents), making it very difficult for people to distinguish the real from the fake. AI can also rescue again to detect fakes.” Rama Akkiraju (IBM Fellow)
AI for Self-Healing and Self-Managing IT Systems
“AI will be more commonly applied to IT data such logs, metrics and tickets, as well as other artifacts of the software development lifecycle such as code, deployment descriptions, change requests, and so on. AIOps is a better IT operations management (AIOps), which includes incident detection, diagnosis and resolution, as well as avoidance. We will see a push toward self-healing and self-managing IT systems.
10 AI Predictions 2022: From Automation and Robots That Clean
