Cognitive systems may bring to mind artificial intelligence’s dark side, one propelled by visions of robots coming to rule over humans like they do in popular sci-fi films such as The Terminator, Ex Machina, and Transformers. But cognitive systems aren’t just for sci-fi movies. In business, cognitive computing holds the possibility of radical transformation by processing data much faster than humans. Here, we explain how the promise of the technology should be navigated: the principles of cognitive computing, factors affecting cognitive computing’s adoption, and how to integrate cognitive computing in business.
To learn more, check out the infographic below created by the Ohio University Online Master of Business Administration program.
Add This Infographic to Your Site
<p style="clear:both;margin-bottom:20px;"><a href="https://onlinemasters.ohio.edu/blog/the-cognitive-business-disruption/" rel="noreferrer" target="_blank"><img src="https://s3.amazonaws.com/utep-uploads/wp-content/uploads/sparkle-box/2018/09/10055856/OU-MBA1-Cognitive-Business-Disruption_final.png" alt="The Cognitive Business Disruption" style="max-width:100%;" /></a></p><p style="clear:both;margin-bottom:20px;"><a href="https://onlinemasters.ohio.edu" rel="noreferrer" target="_blank">Ohio University </a></p>
Principles of Cognitive Computing
Humans and computers are now interacting. This interaction is different than what’s shown in sci-fi, where robots are capable of mimicking humans. In business, robots could help professionals identify and avoid bias, make well-informed decisions, and increase the speed and consistency of decision-making.
According to IBM, AI should serve a distinct purpose. This purpose, whether it’s used in systems, products, or services, must always be under human control. Remember – AI exists to assist humans, not replace them.
There also needs to be a layer of transparency. For AI to work, business leaders need to trust the results. This means there must always be clear answers to AI usage, the data the AI handles, and AI is protecting the data and its insights.
Finally, there needs to be an enhancement of worker skills. AI doesn’t work without humans, so business leaders need to support them by ensuring workers have proper training to work with AI in a safe, secure, and efficient manner.
A Disrupted Future
The successful adoption of cognitive computing depends on numerous factors. For example, many in the field believe that existing tech needs to advance if businesses are really going to benefit from cognitive computing. Fortunately, advancements like natural language processing, neuromorphic computers, unsupervised machine learning algorithms, and virtual reality devices may be already helping this push.
Managing perception is also important. While businesses stand to profit from using cognitive computing, skepticism of futuristic tech may mean a dearth of funding. Businesses can combat the nay-sayers by always grounding their ideas, talking about cognitive computing’s potential importance, and being clear about AIs realties and possible limitations.
Keeping pace with information is another crucial element. The digital universe will reach 40 zettabytes by 2020, which means the adoption of cognitive computing will accelerate. It’s already possible to see that acceleration in action, thanks to the growth in social media and mobile devices.
Additionally, businesses using cognitive computing will likely have to create or be subject to various policies. This can be viewed as an extension of policies around data and privacy, which are continually evolving. In this case, proactively preparing policies could help combat fear, uncertainty, and doubt.
Finally, the skill development is essential. Since cognitive computing doesn’t work without people, businesses need highly skilled workers to carry out the process. However, these workers are often in short supply, particularly workers that specialize in machine learning and natural language processing.
Adopting Cognitive Computing
There are numerous factors for business leaders to consider when it comes to incorporating cognitive computing. IBM offers some good ideas on how to start.
Firstly, it’s important to develop a cognitive strategy to determine where AI should fit among products, services, processes, and operations. Constructing a foundation of useable and reliable data and analysis is also vital. Another key strategical component is the use and proper configuration of cloud services. Additionally, businesses must fine-tune their IT systems for cognitive workloads. Finally, business must make sure the cognitive computing system is secure.
Businesses that incorporate cognitive computing
The financial service company USAA uses cognitive computing to help military members transition to civilian life. The company, which serves 10.4 million current and former US armed forces members and their family, deployed the method to analyze more than 3,000 specialized military documents. The tech also helps new veterans ask situational-specific questions via usaa.com or on a mobile browser.
The health benefits company Wellpoint, Inc, uses cognitive computing to cut down the wait time for the pre-authorization process. It does so by making decisions based on doctor’s notes, patient records, medical annotations, and clinical feedback – decisions that get more efficient over time. This makes it easier for health professionals to keep up with demands.
According to documents obtained by CNBC, Amazon is using its virtual assistant Alexa to apply cognitive computing concepts toward the health and wellness sector. Specifically, they’re using Alexa to help with diabetes management, mother/infant care, and aging support.
Steps to Getting Ready
There are several factors that must be addressed prior to cognitive computing implementation. Businesses must firstly determine what opportunities exist to create more engaging and personalized customer experiences. They must also pinpoint specific data that can help them meet objectives but isn’t being leveraged. Additionally, they need to calculate the cost of their organization relating to non-evidence-based decisions. They also need to determine the benefits gained by detecting hidden data patterns. Finally, they need to figure out their organizational expertise skill gap.
Ultimately, AI isn’t just for movies. Businesses are already reaping bug gains from incorporating cognitive computing into their work, and it doesn’t stop now. If businesses embrace the cognitive disruption, there’s an entire well of untapped potential waiting. By tapping into it, businesses are setting themselves up for growth and economic gain in the digital age.