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Artificial Intelligence

How Collaborative AI Will Enhance Human Skills

AI is a powerful force quickly and radically changing how we live and work. As with any pervasive change, the public is apprehensive about the known and unknown impact of these complex technologies. This apprehension leads (sometimes rightfully) to a focus on the potential negative implications of AI, like worker displacement as well as broader ethical questions brought on by AI applications.

The scope of transitioning to an AI world means it’s imperative to understand the relationship between humans and AI. How we will interact with the technology, and how the technology will interact with us to assist and augment abilities like creativity and intuitive problem-solving are key to maximizing humanity’s potential.


AI promises to free humans from repetitive, mundane, error-laden, and high-risk tasks. Not only does this free the individual to perform duties more interesting to them and profitable for their employers, but it helps reduce costs by eliminating high-resource, low-margin business tasks. The tasks AI can enhance range from accounting to manufacturing to surgical operations.

In many cases, the most effective combined AI and human processes will reflect the human’s strengths, with AI making up the difference. AI can use highly-calibrated measurement systems combined with computer vision and object recognition to help us be more accurate in our daily work. With it, we will more rapidly identify important information in our visual field we may have otherwise missed.

For life and death use cases like medical surgery, this visual enhancement will have a major impact. Innovations like super-resolution for sub-pixel processing for a magnified view of human tissue will be invaluable to patient safety and physician success. This AI-enhanced image magnification allows for more precise cutting to remove more cancer cells while sparing healthy tissue, allowing more cancers to be treated less invasively.


AI will increasingly enhance fundamentally human skills to make us more creative. Pattern recognition, observation, and combining information in novel ways will all be augmented by AI. AI systems are trained to assist in more of these tasks based on growing datasets that are assimilated into so-called deep learning systems. Over time, the computerized parameters developed will mimic human activity at different stages of the creative workflow to automate, expedite, and strengthen it.

The type of creativity at hand isn’t just that which generates famous works of art. It also includes the creativity humans use every day to see problems–and their solutions–in different lights. It also supports better planning and predictive problem-solving, helping identify hurdles sooner or avoid them altogether.

The IP industry is already using automation software to creatively solve problems in real time by systemizing creativity and automating innovation workflows with IQ Ideas Plus™. Improve your understanding of advanced scientific and technological concepts by comparing them to semantically related invention descriptions. Refine ideas and produce high quality invention disclosures in real-time with idea novelty scoring and description editing tools. Users can compare multiple datasets using a weighted semantic system to gauge the relative similarity of technological concepts. Selecting semantic language and determining it is ‘less like’ or ‘more like’ helps target the appropriate technology to assess ideas and discover competitors.

Reduced the total number of results from 272,000 to 53 by relying on’s AI engine to determine relevance and adding two concept modifiers.


AI-driven decision making has the chance to revolutionize business by helping avoid the biases and incomplete data that plague human decision making. AI promises to simplify complex scenarios with multiple, interrelated variables. With sufficiently large datasets and well-constructed algorithms, AI can assist, support, or supplant human decision making where chaotic scenarios can paralyze human decision makers, like in the event of market collapse or natural disaster.

Open source datasets and white box (as opposed to ‘black’) algorithms will allow for easy experimentation with decision making models. Real world simulations with interconnected variables can be set up for multi-step decision making. These simulations could be used to replace or support human decision making, used in adjunct with process mining to reverse engineer workflows to support future human responsiveness.’s innovation suite supports decision making with decision augmentation tools like our Patent Vitality Reports. Concise market intelligence metrics are constructed using comprehensive datasets to calculate predictive scores for litigation risk, monetization potential, and overall patent quality.