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AI: To Go Boldly Where No Man Has Gone Before

By Betsy Burton

 

Artificial Intelligence: To Go Boldly Where No Man Has Gone Before

I couldn’t help myself but to quote the old line from the original Star Trek. But I have been discussing a lot about the impact of artificial intelligence on current held human jobs; what jobs could be lost and what new jobs may be created with it.

And, while these issues are really important, along with the negative potential impacts including increased hacking, fraud, and misinformation, there is also the question what of work artificial intellgience systems that is purely additive.

The reality is, with the advent of Artificial Intelligence-enabled digital labor, there is some work artificial intelligence systems could do that there is no human equivalent, or that humans should not be doing.

Mapping the Bottom of the Ocean

Some of the projects I find really interesting are the efforts to use Artificial Intelligence to map the bottom of the ocean. There is a project called Seabed 2030 that is currently working on just that.

Think about it, the oceans make up 70% of the world surface, and we have only mapped 20% of that. And it isn’t all that far distant of an issue. Where I live, there are large parts of the Monterey Bay that are uncharted because the bay is so deep. 

The Monterey Bay Aquarium Research Institute (MBARI) is using Artificial Intelligence to help them process and analyze thousands of hours of ocean images. Their goal is to use this work to better understand the types of life is in the bay and use this information to help guide policies on resource usage and sustainability. 

Both of these are examples of Artificial Intelligence performing a task that humans can’t take on.

AI and Micro Money Laundering

Catching money laundering has been a complex and difficult task for financial services organizations, investigative bodies (FBI, DHS, etc.) and regulators. In many cases, it is the large transfers of funds or significant real-estate purchases that get the most attention. 

As a result, criminal elements have taken to micro money laundering to evade detection. This is where Artificial Intelligence has a role that humans really couldn’t match. 

With micro money laundering, money is moved around to a very large number of accounts in small random amounts. Money laundering looks like any business dealing with daily transactions. 

Artificial Intelligence can be used to detect frequent small deposits just below reporting thresholds, a sudden surge in account activity or multiple linked accounts showing similar transaction patterns.

Bottom Line 

There are a number of security, privacy, copyright issues, ethical use, misinformation, and disinformation issues when it comes to Artificial Intelligence. There are also issues related to replacing or augmenting human workers, and what impact that has on diverse economies. And in addition, there are some jobs AI systems will take on that there is no human equivalent.

We held our Aragon Research Transform Tour presentation this morning related to this topic. 

The big take away is that Artificial Intelligence is coming and will change how we work. Business and technology leaders must start understanding now how they might use AI and where they should not be using AI. There’s no stopping it. Your users and business leaders will adopt it so it’s critical that leaders and executives define parameters for this usage. 

Keep your eye out for a note that I’m about to release. It provides sample principles for the use of Artificial Intelligence. I’m hoping that this will help organizations define guidelines and guardrails for how they should leverage AI and what guidance to provide within their organization.


Decoding the Role:Artificial Intelligence Architect vs. Solution & Application Architects

Adopting Artificial Intelligence-enabled technologies is as much a people, process, organization, and strategy issue as it is about technology. The best AI-enabled solution will go nowhere if it doesn’t address a future-state business need and is accepted by users. Adopting AI-based solutions requires outside-in customer, user, and business thinking; not inside-out technology first thinking. Adopting AI requires a business and future-focused architect to help guide the integration of people, process, information, solutions and AI.

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Missed the previous installments? Catch up here:

Blog 35: Case Study: Business Transformation Hits a Roadblock, What do You Do?

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Blog 36: What Do You Do When Management Won’t Listen?

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Blog 37: How Do We Organize for Business Transformation?

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Blog 38: New 2023 Market Globe: tPaaS Market Will Surpass the iPaaS Market

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Blog 39: A Leader in the iPaaS Market but Not tPaaS – Here’s Why

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Blog 40: Low-Code/No-Code Is a Feature Not a Product

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Blog 41: Google IO Impressions: Is Generative AI Business Transformative?

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Blog 42: What Size Company is a Good Fit for tPaaS?

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Blog 43: Brand New Detailed tPaaS Provider Comparison

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Blog 44: Enterprise Architects: Generative AI is Real Don’t Miss This Opportunity

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Blog 45: Join Me Next Week For Aragon Transform Tour Presentation on Digital Labor

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Blog 46: Are You Prepared to Manage Your Digital Labor Force?

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Blog 47: Digital Labor is Coming: Don’t Be Caught Unprepared

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Blog 48: You Need An Artificial Intelligence Architect Now

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Blog 50: Business Leaders, How Do You Make Technology Decisions?

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Blog 51: SnapLogic’s Generative Integration

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Blog 52: Prepping Your Organization for Artificial Intelligence—How To Skill Up Your Workforce

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Blog 53: Is Your Data Artificial Intelligence Ready?

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Blog 54: Zoom’s Privacy Misstep: Is theirArtificial Intelligence Being Trained with Your Information?

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Blog 55: The State of Copyrights and Generative AI

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Blog 56: Why Listening to Your Current Customers Can Derail Innovation

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Blog 57: HOT: New Artificial Intelligence and Business Transformation Research

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Blog 58: Are We Turning Off Our Brains in Favor of Artificial Intelligence?

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Blog 59: The Impact of Artificial Intelligence on the Workforce

Stay tuned! We publish a new blog every week.

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