Over the last several years, AI has been seeping into nearly every industry, changing how humans and machines perform and interact day-to-day. But in the coming months, the hype around AI will make way for more realistic approaches for implementing it across organizations. As people awaken to the idea that AI can be designed to augment their natural abilities, we will see AI be more widely adopted in the workplace. Find out more of what’s to come in the AI field from some of our very own Cogicians. The key for AI’s increasing success will be centered around enabling a technological solution to resolve a key business problem. Companies can no longer experiment, deploying AI for the sake of it, in hopes that it improves business operations.

 

Josh Feast | CEO of Cogito:

The Year of Demystifying AI

Society will push for the demystification of AI and demand a better understanding of what technology is being built, and greater transparency into how it is being used. In recent years, there has been an apparent shift in mindset across our society when it comes to AI, especially regarding privacy concerns. As a result, technology creators will have to embrace full transparency and responsibility to ensure privacy rights are respected and that the technology is being used in a valuable and ethical way. As transparency increases, people will better understand that AI is not an all-encompassing term for machines that can replicate and act like a complete human, but rather a more explicit set of functionalities that can better automate simple tasks and help augment people who are performing more complex activities.

Emotional Intelligence Will Become a Competitive Differentiator

Emotional intelligence (EQ) will become mainstream in 2019, as certain applications of AI better handle mundane tasks and humans strive to cope with the increasing pressures of modern life. EQ will become a more critical skill set for executing higher order tasks and innovative thinking. It will be the key differentiator for organizations, leading to more companies actively fostering EQ amongst their employees. This emotional initiative will enhance workplace culture, improve productivity, drive innovation and tighten the bond between an organization and its customers.

Every Professional Will Have an AI Coach

In the near future, organizations will increasingly turn to AI to augment humans in areas previously not considered possible. Previously, the majority of organizations have leveraged AI to eliminate simple tasks and not to actually help humans be better humans. Through thoughtful integration, however, AI can become a friendly point of contact and change the way we interact in virtual space, ultimately making people better versions of themselves.

By taking “humanness” — emotion, fatigue, stress, etc. — into account when adopting AI technologies, organizations will be able to foster more empathetic and human-centric organizations. The implementation of AI will undoubtedly help companies better quantify emotions and understand the nuances of human communication, which will enable better, more “human,” business decisions.

Closed Loop Systems are Best Positioned to Move AI Forward

Closed loop systems will become standard for improving AI’s capabilities. Systems that can measure, provide feedback, observe the results and learn from the usage will help position AI to become smarter and more effective at achieving a desired result. If the usage of the outputs generated from AI are disconnected from the capturing and learning mechanisms, there will be a barrier for how quickly and effectively a given set of machine learning models can improve.

 

Dr. John Kane - VO Data-Science and Signal Design at Cogito

John Kane | Distinguished Scientist, Machine Learning at Cogito:

Democratization of Machine Learning

Despite “democratization of machine learning” solutions and increased research attention on automated machine learning (for instance Google’s recent AdaNet autoML system) there will continue to be a growth in demand for machine learning and deep learning specialists in the year ahead. For modeling problems that are considered “solved,” these automated modeling systems will be increasingly adopted; but for new modeling problems or for areas which are still very much “unsolved,” there will be an increasing need for skilled scientists and engineers. In 2019, the industry (and academic institutions) should focus on developing resources, such as courses on ML and AI, and continue to invest in addressing the current skills gap to keep up with the ever-increasing labor demand.

Discrimination and Bias in ML/AI

Businesses and society in general are becoming increasingly concerned about discrimination and bias introduced by machine learning and AI. This is with good reason, as there have been several cases reported of credit rating algorithms treating people from certain demographics unfairly and image processing models incorrectly classifying the color of people’s skin. As a result, there is an onus on technology companies to implement processes which mitigate bias in their AI systems.

Throughout the rest of 2019, companies should adopt and implement a model development protocol, which follows the FAIR framework. This framework involves using data collection and machine learning techniques to reduce the effect of bias in models. Failing to implement such protocol will result in negative perceptions from the public and customers, as well as ineffective applications.

Machine Learning Models Will Become More Context-Aware

In 2019, context awareness will become even more important for machine learning. Machine learning models will need to know more about context (e.g., what device is being used, what prior information is known about the user) and adapt accordingly. There will be increased interest in understanding the emotional and health state of users of these technologies, along with the need for contextually appropriate responses in the year ahead. As the context improves so will the specific assistance AI can deliver towards achieving a positive outcome for a given situation.

For more predictions from John Kane, check out his article for VMblog here.

 

Dr. Ali Azarbayejani - Chief Technology Officer at Cogito

Ali Azarbayejani | CTO of Cogito:

The Human and Machine Relationship

By nature, and design, humans and computers have different strengths. In the coming months, we will see the human-machine relationship evolve to become more sophisticated and exist in a more symbiotic manner. Companies will embrace the skills of their human workforce and AI creators will develop technology that bolsters humans’ natural abilities.

Why the AI Hype is Over

The hype is over. “AI” as a term has cluttered the technology space and the use of it is actually doing a disservice to the market. But in the second half of 2019, we will gain clarity around what AI means for both society and businesses. Up until this point, the fear around AI stems from miscommunication around its reality and exaggerated claims of a machine takeover, but the technology can actually help augment a person’s natural abilities and increase productivity, making them better versions of themselves. Soon, AI won’t just be a buzzword and the perception around the technology will shift for the better.

Steve Kraus
Steve Kraus

Steve brings over twenty years of experience in marketing, selling, and delivering customer engagement solutions to the world’s most customer-centric organizations. Prior to joining Cogito, Steve led product marketing for Pegasystems CRM suite of applications, growing the suite from a niche player into a recognized leader for marketing, sales, and service applications. Steve led go-to-market activities for Verint (formerly KANA Software), serving as the General Manager for Verint’s customer experience management applications, and led product marketing and strategy for Chordiant Software’s CRM applications. Earlier in his career, Steve managed consulting teams within Ernst &Young. He has a B.A. in Economics and Accounting from The College of The Holy Cross.