Why is A.I. So Scary?

When we think of artificial intelligence, a lot of us think of what we see coming from Hollywood. Movies like the Terminator, War Games and the Matrix color our imaginations to see A.I. as a villain and something to be feared. But it shouldn’t be so scary.

“AI is everywhere in tech right now, said to be powering everything from your TV to your toothbrush. In short, it’s making decisions that affect your life whether you like it or not.” 1

Today we all walk around with A.I. in our pockets (Siri), running our homes (Alexa), giving us directions (Waze), how we watch TV (Netflix) and soon in all of our cars (Waymo). So why the disconnect? What is about the way we use A.I. in our personal lives makes it so easy to use and not nightmare inducing?

At this point in time, we’ve only scratched the surface of examples of A.I. in day-to-day life. Specific industries and hobbies have habitual interaction with A.I. far beyond what’s explored in this book. For example, casual chess players regularly use A.I. powered chess engines to analyze their games and practice tactics, and bloggers often use mailing-list services that use a machine to optimize reader engagement and open-rates. 2

In fact, the applications of artificial intelligence is already so ingrained in what we do every day, it’s just mostly out of sight or at least not staring us in the face. We just have this double standard between what we see as harmless and what we see as a menace.

How will A.I. affect daily life on a grand scale in the near future? Futurist and Wired magazine co-founder Kevin Kelly predicts that, as AI becomes more deeply integrated in our lives, it will become the new infrastructure powering a second industrial revolution. ”The actual path of a raindrop as it goes down the valley is unpredictable, but the general direction is inevitable,” says Kelly — and technology is much the same, driven by patterns that are surprising but inevitable.

This genie is not going back in the bottle. Over the next 20 years, he says, “our penchant for making things smarter and smarter will have a profound impact on nearly everything we do. “Kelly explores three trends in AI we need to understand in order to embrace it and steer its development. “The most popular AI product 20 years from now that everyone uses has not been invented yet,” Kelly says. “That means that you’re not late.” 3

With this in mind, I want to bring things back to ground level and share with you my story about how I got started with artificial intelligence. The idea behind my next book is really to explain to you my path, from where I started with data and technology to where I am at now. As I share my story I will also explain what I’ve seen across hundreds of businesses, and highlight the importance of starting to think about how to use artificial intelligence for massive success.

Daniel Meyer heads Sonic Analytics, an analytics firm with offices in Manila, the San Francisco Bay Area and Ocala, FL. With over 20 years in Big Data, Dan is one of the most sought-after public speakers in Asia and offers big data coaching and analytics training seminarson both sides of the Pacific. Dan has also recently joined the Powerteam International family as a small business analytics resource speaker.

Sonic Analytics(www.sonicanalytics.com) brings big data analytics solutions like business intelligence, business dashboards and data storytelling to small and medium sized organizations looking to enhance their data-driven decision-making capabilities. We also advocate the use of analytics for civic responsibility through training, consulting and education.

As citizens of this great democracy, we need to look at the data (analytics), plan a course of action (strategy) and share our data-driven viewpoints (presentation). This approach to a data savvy work force starts in school. So, we started an internship program to empower our youth to use Analytics, plan Strategy and Present their insights… ASP!

When not training current and future analysts, you can find Dan championing the use of analytics to empower data-driven citizenship by volunteering his expertise with schools and non-profits dedicated to evidence-based social progress like Saint Leo University’s Women in STEAM 2020 Conference.


Augmented Analytics: A.I., Machine Learning & Predictive Analytics

I recently spoke about Augmented Analytics: Trends in Artificial Intelligence, Machine Learning and Predictive Analytics.

Much has been made about the business implications of recent, rapid advancements in cognitive computing.

It’s no longer just a pair of eyes scanning data.

We now face the reality of advanced analytics tools to help human knowledge workers glean actionable insight from vast and deep lakes of historical, transactional and machine-generated information.

This is augmented analytics and it includes concepts like predictive analytics, machine learning and A.I. If these are terms you have a general familiarity with, but haven’t spent much time thinking about how the related to big data, analytics and data science, then you should.

Business analytics today can be done with MS Excel and maybe a good BI tool, but business analytics tomorrow will require augmented analytics skills.


Analytics in the Philippines – The Philippines is at the center of the action when it comes to solutions to the global need for analytics. Blessed with a solid foundation of young, educated and English speaking workforce, companies around the world are look for Filipino analytics talent to fill analytics positions.

DMAIPH was set up to facilitate these solutions and bring the talent and the business together. And that is exactly why I wrote Putting Your Data to Work, the first analytics guidebook designed specifically for the Philippines. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can help you take advantage of this unique global opportunity.

Top Data Science & Analytics Skills in Demand: 2017 vs 2022

One question I get asked a lot are what are the best skills to master for Data Science & Analytics (DSA) jobs right now?

Another question is what skills will be in demand five years from now.

With both questions, most of the ones asking are looking for specific applications or tools to learn. Often my reply is that it really doesn’t matter which tool or application you use as much as you get practical experience working with data.

My point is that job titles and technical skill sets come and go as technology evolves… what you really need to do is be in a place where your curiosity and critical thinking are continuously challenged. It helps to also be somewhere that encourages new solutions and has a culture that fosters innovation.

Not easy to find, but thats more important to me then what you learn now. That said, I still have to answer the questions with some sense of what to learn and master so…

Here are some of the top DSA skills needed right now:

  • Management Reporting
  • Advanced Excel
  • Familiarity with Business Intelligence Tools
  • SQL Coding for Teradata Databases
  • Transforming Data Warehouses into Data Lakes
  • Business Dashboards and Data Visualization with Tableau
  • Predictive Analytics with R and Azure
  • Predictive Model Building with SPSS
  • Data Storytelling

By no means a exclusive list… if you do a quick search of job posting for DSA professionals you will not find two job posts with the exact same requirements.  From where I sit, these are just the ones I see a lot.

When it comes to the future, I did a quick search and came up with this list…

Here are some of the top DSA skills likely needed over the next 5 years.

  • Natural Language Generation and Text Analytics
  • Human/BioMetric Analytics
  • Machine Learning
  • Prescriptive Analytics
  • Chat Bot Design and Maintenance
  • AI Virtual Assistants Design and Programming
  • IoT Sensor Analytics

Again… not even close to a complete list, but you can get a sense of where things are going.

Assuming most companies mature past the basic analytics phase and that we continue moving towards AI solutions at the current pace, there will be a lot of new analyst jobs out there with new titles. Data Scientists will be busy solving a wide range of data challenges that currently still seem like Science Fiction today.

At least that’s my take as of now.

It will change.


The Augment BPO Data Science and Analytics Advocacy Project (Augment BPO) is empowering BPO Companies, Executives, and Workers in the Philippines to prepare for and address the clear and present danger posed by Artificial Intelligence Chatbots (AI Chatbots) to BPO revenue growth and jobs through Data Science and Analytics strategy planning, awareness building and upskill training.