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The Human AI: Amplifying Human Interactions Using Conversational Intelligence


In today’s world, new technologies are benefiting us in ways we could’ve scarcely imagined even 10 years ago. Yet, we now also have important judgments and distinctions to make in how we allow these new technologies to impact our lives. Conversational Intelligence is a unique kind of resource in this new tech world.  It presents an opportunity to pursue automation and insights in a way that is both mindful of the technology’s imprint and influence as well as its potential negative impact.

Conversational Intelligence (CI) tools can bring insights in a way that is directed and controlled by human initiative while still providing the benefits of automation. It complements the strengths of our human communities while guarding against some of the worst-case scenarios we could experience through poorly conceived AI.

Harnessing Speech-to-Text Technology

Like it or not, speech-to-text is already here.

We’re using it in a wide array of technologies from our personal smartphone devices to videoconferencing to other work-related applications. The missing piece lay in how we take all of that transcribed audio and get actionable, valuable insights. This doesn’t happen without intentionality and that’s where conversational intelligence comes in.

The tools that define CI are groundbreaking in a profound way.

For over a decade engineers have been laying the groundwork for speech technology by mapping our human lexicons, parsing audio inputs, and overcoming all of the challenges that are inherent to this endeavor. Insight mining is the next logical step in the development of speech technologies but the tools to make that reality have been largely absent until recently.

CI tools are the missing link that fundamentally changes how we benefit from the already established work in the field of natural language processing. It validates what “machines” bring to the table as centered on our values and works towards our goals and objectives. It represents an ethical kind of AI.

Creating Supervised and Assistive Technology

The key point when it comes to conversational intelligence and how it is applied is intentionality.  CI tools are inherently controlled by human thought and initiative. This isn’t a rogue technology that can cycle out of control or provide poorly targeted results that skew projects with harmful results. It is, rather, uniquely suited to contribute to an approach that supports ethical AI in business.

When combined with Conversational Intelligence, Conversational AI can open up a world of possibilities whether it’s new intents, real-time knowledge creation, or training. With the breadth of conversational metadata available, companies can leverage the use of “virtual assistants” and CI to deploy systems that will optimize enterprise IT in a deliberate and controlled way.

Engineers and other experts worry that machine bias in some areas of ML could complicate what we get out of smart computing. If the program is not calibrated well, its input could be poorly targeted, or, even unsettling.

ML programs often run up against what experts call the “value learning problem” – the orientation of a program without explicit programming direction.

With CI, however, this problem is not in play.

Everything in conversational intelligence is gleaned directly from human operators – so it’s accurate to call this an assistive technology or human/AI collaboration. That’s a big distinction to make when separating conversational intelligence tools from machine learning systems that are self-generating.

There are many examples of previously pioneering, self-generating AI bots that had to be quickly removed from sight when they started going off on tangents that were insensitive or harmful. CI tools are insulated from this because they are innately focused on magnifying real human thought and cognitive work processes.

Enhancing Workflows and Business Models

To determine the value that CI generates think about all that you discuss on a typical business call. People have great ideas, – or, “aha moments”  – and, then, others chime in. At the end of the call, though,  you’re often left with whatever immediate impressions you have or, more often, what you are able to glean from some hastily scribbled notes.

Even an exact transcript of a call jumbles the best ideas and concepts into a raw data stream. This can include introductions, social niceties, a review of already known data points, etc.  All of this clouds the ability to generate meaningful insights.

Cutting through the noise to get to the signal is the critically important part of what CI enables. CI also has the added benefit of being flexible enough to be used in conjunction with other tools.

One such conjunctive technology that offers a lot of potential is the convolutional neural network or CNN. We as a tech community have put a lot of work into CNNs, which allow ML programs to effectively “see” and identify objects and contours in images.

Imagine if you could take a phone call or Slack chat and, after entering it into a CI program, get back pictures, Gantt charts, or spreadsheets of all the things you were discussing! That would be an incredibly powerful business intelligence asset.

Interoperability of Tools

Another key design aspect of CI contributions is the ability to deliver powerful business insights seamlessly when combined with existing technologies that we use every day,

What about Slack and MS Teams, platforms that are increasingly used in this age of remote collaborative work? What about key email platforms like Gmail and Outlook?

When CI tools accommodate all of those interactions with platform compatibility, they optimize the value that they bring to human decision-makers.

All of these decision support tools are key to how CI augments positives without creating unintended negatives. It works on the principle of direct human input – but it performs the actions or work that humans don’t want to do, or, may not do efficiently themselves. Think about how these models can apply to your business.   They provide human-directed insights with the power of automation and the flexibility to support existing workflows.   This kind of AI technology enhances human communities while at the same time never posing a threat.   In this sense, it is a unique form of AI.

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