Our AI Impact

 for the health of people

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 Our AI Impact

 for the health of planet

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 Our AI Impact

 for the health of business

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FOR THE HEALTH OF PEOPLE: EQUITY
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“The work [with Synaptiq] is unprecedented in its scale and potential impact,” Mortenson Center’s Managing Director Laura MacDonald MacDonald said. “It ties together our center’s strengths in impact evaluation and sensor deployment to generate evidence that informs development tools, policy, and practice.” 
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    ⇲ Implement & Scale
    DATA STRATEGY
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    A startup in digital health trained a risk model to open up a robust, precise, and scalable processing pipeline so providers could move faster, and patients could move with confidence after spinal surgery. 
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      PREDICTIVE ANALYTICS
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      Thwart errors, relieve in-take form exhaustion, and build a more accurate data picture for patients in chronic pain? Those who prefer the natural albeit comprehensive path to health and wellness said: sign me up. 
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        MACHINE VISION
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        Using a dynamic machine vision solution for detecting plaques in the carotid artery and providing care teams with rapid answers, saves lives with early disease detection and monitoring. 
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          INTELLIGENT AUTOMATION
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          This global law firm needed to be fast, adaptive, and provide unrivaled client service under pressure, intelligent automation did just that plus it made time for what matters most: meaningful human interactions. 
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            Mushrooms, Goats, and Machine Learning: What do they all have in common? You may never know unless you get started exploring the fundamentals of Machine Learning with Dr. Tim Oates, Synaptiq's Chief Data Scientist. You can read and visualize his new book in Python, tinker with inputs, and practice machine learning techniques for free. 

            Start Chapter 1 Now ⇢ 

             

              How Should My Company Prioritize AIQ™ Capabilities?

               

                 

                 

                 

                Start With Your AIQ Score

                  4 min read

                  Reality-Checking AI Hype: Two Things You Should Know

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                  Beware the "Magic Bullet" Hype Train

                  There’s a lot of hype about artificial intelligence (AI). Maybe you’ve heard that it can triple, quintuple, centuple your productivity overnight; it can replace every employee in your organization; it can solve your problems with the slightest (automated) flick of its finger. But that’s not reality. AI is a tool, not a magic bullet.

                  In 2021, the McKinsey Global Survey polled thousands of business leaders across industries and found that the businesses seeing the highest earnings boost from AI are also those spending the most efficiently on AI.

                  AI adoption is growing: “56 percent of all [McKinsey Global Survey] respondents report AI adoption in at least one function, up from 50 percent in 2020.” As a result, simply “having” AI is no longer a competitive advantage. Businesses that not only “have” but also use AI cost-effectively and efficiently are the real market winners.

                  How to Recognize Innovation

                  If your business hasn’t yet adopted AI (or tried and failed in the past), then the question on your mind is probably something like, "How do you recognize what's worth your money, and what's not?" It’s hard to tell without experience, and mercenary vendors won’t hesitate to sell you hype with a price tag marked, "innovation.”

                  That’s why Synaptiq created  AIQ™, "Artificial Intelligence Quotient", a score that determines your organization's readiness for AI and overall data maturity to help companies succeed with their AI initiatives. You can read more about AIQ on our blog, or take our AIQ assessment now in order to quantify your organization's AI readiness.

                   

                   

                  BUT! Although AIQ is a valuable metric, raising your organization's AIQ shouldn’t take priority over other business objectives. It's important to remember that AI is not a magic bullet. It won’t solve your problems overnight—especially if those problems sound something like, “We’re broke because we over-invested in AI hype!”

                  Here are two things to keep in mind:

                  #1. Low AIQ Is Not Necessarily Bad

                  Sometimes, it means a blank slate: the perfect foundation for building something better. Unlike IQ, AIQ can increase significantly with strategic change. No business is “born” with a genius AIQ!

                  If your business has a low AIQ, don't start trying to raise it right away. First, it’s essential to consider whether or not (and why)  a future AI endeavor is worth the investment. The following questions are a good place to start:

                  • How will AI help you achieve your near or long-term business objectives?

                  • What will the cost of raising AIQ be versus the benefit?

                  AI is the future, and the future is approaching—fast. But it won’t arrive tomorrow. If your business is better prepared to raise its AIQ three months, six months, or even a year from today, then wait. Committing wholeheartedly to AI readiness in the future is preferable to a half-hearted effort now that could lead to failure. The consequences of a poor initial attempt could breed AI paranoia, potentially hindering your organization for a prolonged period.

                  #2. High AIQ Does Not Guarantee Success.

                  Imagine a track athlete who stumbles at the final hurdle - that's the challenge of AIQ.

                  What's this last hurdle in AIQ? It's about utilizing your AI readiness effectively. Consider the case of a fictitious high-AIQ business, which we'll call Smartly. It excelled at all the elements of AIQ, especially data sourcing: a key component of AI readiness. Consequently, Smartly's leadership expected smooth sailing to AI implementation.

                  But, as Smartly was about to launch its first AI project, it made a critical error. Overconfidently, its implementation team swapped their excellent external data out for inferior in-house data. The result? Smartly's AI project failed.

                  The issue was implementation. Despite its high AIQ and data sourcing expertise, Smartly didn’t apply these strengths in its project. Its team reverted to old habits, using subpar in-house data instead of the superior third-party data they had. The takeaway is this: If your business has a high AIQ, make sure to leverage it fully!

                   

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                  About Synaptiq

                  Synaptiq is an AI and data science consultancy based in Portland, Oregon. We collaborate with our clients to develop human-centered products and solutions. We uphold a strong commitment to ethics and innovation. 

                  Contact us if you have a problem to solve, a process to refine, or a question to ask.

                  You can learn more about our story through our past projects, blog, or podcast

                  Additional Reading:

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