Thursday, November 26, 2020

2020 Christmas Specials

Image by Jan Vašek from Pixabay



 I put this list of 2020 Christmas Specials together for family, so I thought I would share it with everyone.

I'll add items as I find them. If you have any to add, let me know or add a comment here.

Before I give dates, here are a few links: 




Friday November 27

Grinch cartoon 8pm ET NBC

Minions 8:30pm ET NBC

Charlie Brown Thanksgiving PBS

Monday November 30

Disney Sing along 8pm ABC

Wednesday dec 2

New York tree lighting NBC 

December 9

Live grinch ABC

December 13
The Chosen Christmas Special 8PM ET

December 16,17, 23,24,25

December 25
Disney Christmas Celebration

January 1
Rose Bowl Parade

Do you know of others?

Friday, October 30, 2020

The Power of Soft Skills

Illustration Copyright 2020 Glenn Witmore

I'm doing a FREE webinar on "The Power Of Soft Skills" on Nov. 17, 2020. 

You can register here.

This blogpost provides some reference information for the presentation.

I'll add more items here as they become available. 

Please do comment with your thoughts!

There are lots of movies about superheroes, so I want you to know that…
You can be a superpower through the use of the power of soft skills!

My friend, Glenn Witmore, created this graphic for my presentation. He’s a professional comic book artist who has worked on major superhero licenses and owns where you can find more about him and his work.
As you can tell, Glenn didn’t use my likeness to create the character here in the foreground LOL 

Wikipedia provides a top10 list of softskills.
Maybe it will help to talk about hard skills. Hard Skills are those we learn from classes or get certified in, like Project Management, AI, Python, Scrum Master, SAFe Agilist or even using a tool such as spreadsheets.

What is a common thread in soft skills? People! Dealing with people! Sometimes they are called “People Skills”.
How do they vary from “Hard Skills”?

Active listening:

Four Stages of Competence

By asking questions we produce some stress which can motivate people to make improvements.

Yerkes-Dodson Law – becoming stressed to the point of distress

Stress can turn into distress when it becomes overwhelming and productivity will decrease. 

Have you ever had this happen?

Freedom Ladder:

Maslow's Hierarchy:  

Altruism – caring for the needs of another while sacrificing your own needs.

John Kotter’s books “Leading Change” “The Heart of Change” and his website

7 Habits of Highly Effective People” by Franklin Covey 

Design Thinking – IBM information and course (digital badge option)

Why soft Skills are so difficult to teach

“Emotional Intelligence: no soft skill”

Never Eat Alone – Keith Ferrazzi
How to Win Friends and Influence People – Dale Carnegie

 Please add your comments!



Tuesday, September 08, 2020

How We Helped Each Other Today


Image by Gerd Altmann from Pixabay

Emmaus Work Connectors had our monthly meeting this evening.

The group is about helping each other in our work journey.

We started out with the following encouraging words and a brief prayer:

Isaiah 41:10. “Do not fear, for I am with you; do not anxiously look about you, for I am your God. ...
Psalm 37:23-25. “The steps of a man are established by the Lord, and He delights in his way.

We then started with the question:

  • In one minute, explain what would be the best outcome of this time together tonight?

Everyone took a turn. Some people were there to help others. Some had things they were working on that they needed help with. Here are a few highlights of the meeting.

1. We talked about how to get motivation to get to our goals. This article was shared: "How To Master Your Goals With The Ulysses Pact" on the trello blog.

Someone mentioned that this was along the lines of a book they just picked up titled "indistractable" by Nir Eyal

2. One person was working on an introduction of themselves to a class they are taking.
We worked together on ideas of how to write a good introduction. 

It was mentioned that telling a story makes it more memorable. One person remembered that tomorrow the Vyond team is offering a "tour" online (for free) that goes for several weeks on Wednesdays called the "Virtual Story Telling Tour".

We also discussed how we can use mind-mapping for brainstorming in writing ( which a few people in our group are doing ) or presenting (which I do a lot of)

We talked about creating an effective headline - for LinkedIn and for our introduction:

3. It was mentioned that in a future monthly meeting (or in one of the weekly small group meetings) we could work together on our LinkedIn headlines as a task to help each other with.


These meetings are glitzy, they're not all that structured, but they are helpful to the people who participate by either sharing their needs or helping others. And, just like one of our main goals states, by helping each other, we create strong net-working bonds.  We use the team "Net-working" because we network by working together on each other's work-journey goals.

Maybe you'll consider joining us at some point. 

Please comment here about what you have found to be effective in your work-journey or in helping others.

Sign up and find details here.

Saturday, May 30, 2020

Choir Festival Great Moments from Ocean Grove Camp Meeting Assosication ...

Here's one of the things I've been working on during this pandemic: Volunteer work for Premier / Watch Parties for the Ocean Grove Camp Meeting Association. Please tune in and invite others.

Website is

Tuesday, May 05, 2020

Project Management and Artificial Intelligence

I am posting this as a supplement to several talks I'm giving on "Project Management and Artificial Intelligence"

I suggest you look at this previous blog post where I provided lots of information on AI and Project Management.

About AI:
Examples of AI:
  • Chatbots
  • Virtual Assistants: Alexa, Google Assistant, Siri, Cortana
  • RPA
  • Robots (e.g. Boston Dynamics and DARPA Robotics Challenge) and Cobots
  • Recommendation Engines: Amazon, Netflix, etc.
  • Gaming (Go, Chess, Jeopardy, video games)
  • Speech recognition and speech synthesis
  • NLP – analyzing documents/ Knowledge Base
  • Autonomous vehicles and semi-autonomous
  • Expert systems / Decision support systems
  • Medical diagnosis (oncology, radiology)
  • Visual recognition (including Facial recognition)
  • Spam filtering
  • Fraud detection
  • Digital Workers - e.g. ipsoft
  • : Everyday Examples of Artificial Intelligence and Machine Learning
Fields of AI:
Subfields of AI:

Types of AI
  •  Forbes (June 2019) : 7 Types Of Artificial Intelligence
    •  AI Classification
      • Classification based on likeness to Human Mind
        • Reactive machines – no memory. e,g, big blue that mastered chess
        • Limited memory - chatbots, self-driving cars, VAs
        • Theory of Mind -  understands needs, emotions, beliefs
        • Self-Aware - human-like intelligence and self-awareness
      • Technical Classification
        • Artificial Narrow Intelligence (ANI) aka Weak AI or Narrow AI: this is AI specialized in it's application area (e.g. what is available now)
        • Artificial General Intelligence (AGI) aka Stong AI: self-learning in general areas like a human - "Technical Singularity"
        • Artificial Superintelligence (ASI) – more than human
    • Medium:  Types of Machine Learning Algorithms You Should Know
      • Supervised Learning - Human does the teaching (labeled training)
      • Unsupervised learning - learns on it's own to mine data for rules, patterns and groupings
      • semi-supervised learning - lies between the two above: Human provides some training and the system extrapolates from there.
      • reinforcement learning - Human provides a "reinforcement signal" (a "goal") and the AI "agent" interacts with the environment to see which experiences optimize the reinforcement. This is used for Gaming (Go, Chess), and autonomous vehicles.
    • KDnuggets: AI Knowledge Map: How To Classify AI Technologies

Testing AI:
  • Hold-Out (aka "Blind data") test set Vs. Cross-Validation - Medium
  • K-Fold Cross Validation - Wikipedia
Project Management and AI

Will AI take away my PM job?

I suggest you look at this previous blog post where I provided lots of information on AI and Project Management. 

What comments or additions do you have on this information?

Tuesday, April 21, 2020

What you Can Learn from the Panel on Artificial Intelligence and Project Management

What you Can Learn from the Panel on Artificial Intelligence and Project Management

In February 2020, I was honored to be on the AI Panel discussion at the New Jersey Chapter of Project Management International. George Pace was the moderator and serving on the panel with me was Sandipan Gagopadhyay, David Dalessandro, and Mike Moran. I was selected due to my work managing AI projects in three different companies.

The discussion started out about AI in general and then focused on how Project Management relates to AI. Here are a few of the main points made by the discussion. Thanks to the panelists who have provided additional input below.

Discussion of Four Example Articles on AI The following articles were provided to the chapter members in advance of the meeting. While the panel didn't delve into any particular one in a lot of detail, they were discussed in general. We will explore some of the general intents of these articles in more detail below.

Will It Take Away Jobs?
(Mike Moran provided the following section of this article)
In a sense, AI is a personality test. Some predict that we will have much more leisure time. Others claim that we will all be unemployed. Those two statements are actually the same prediction. It just depends on whether you are an optimist or a pessimist.

What's historically true is that we humans have a difficult time predicting the effects of technology. We are worried about how all the things we are doing now might go away, but we fail to imagine all the new things that will need to be done. In 1790, 90% of the US workforce were farmers. In 1990, it was under 3%. Unemployment wasn't 87%. And today we produce oodles more food than we did in 1790. And the 1990 workforce included droves of women not in the 1790 workforce. What really happened is that technology has made it possible for fewer people to do the things that many people were once needed for, while the rest found other ways to be useful. Technology tends to do that, even if we think every new technology could be the apocalypse. Maybe someday that will be true, but it's probably not that way to bet.

Some people will certainly lose their jobs someday because AI automates away their jobs. But for most people, AI will automate tasks that they currently perform, not their entire job. The people who will lose their jobs to AI are the people who refuse to use AI. They will lose their jobs to those that do.

Take self-driving cars as an example. Despite the hype, there are many thorny issues that need to be resolved for self-driving cars to be more than just a novelty--insurance coverage, changes to roadways, and how parking is configured are just a few. But that's not the real story of AI when it comes to driving. The real story is that AI makes humans better drivers. Many new cars can parallel park themselves. They can tell you when another car is in your blind spot. Or when you are weaving out of your lane. They can apply the brakes in an emergency faster than you can.

Most AI is like that. It doesn't take away your job. It makes you better at your job.

(Thanks Mike for that insight! I agree with that perspective. AI is a work augmentation tool. If AI ever develops to the point of taking away Project Management jobs, I think we have a lot more to be concerned about than our jobs! For more information on this subject, I am providing this article titled "How AI Is Creating Jobs Not Killing Them For Low-Skilled Workers?" on Medium.  Mike's writing reminds me of the phrase “self-fulfilling prophecy.” Some people believe AI will help them in their work and so they embrace it, while others believe it will take their job away, so they ignore it. It's like the quote attributed to Henry Ford: “Whether you think you can or you think you can’t – you’re right!”)

AI needs data and AI is not Magic Pixie dust
  • Some people have the misconception that you can "sprinkle a bit of AI" on something and it automatically becomes magical -it's not that easy and not that magical
  • The AI used in Chatbots, Facial Recognition and image recognition is called "Supervised learning".  For example, if we were training AI to recognize photos of dogs Vs. Cats, it would need a human to manually "label" lots of pictures as dogs and cats. Then the AI uses that information to identify new pictures as either dogs or cats. 
  • I mentioned something during the panel discussion that astonished many in the audience. I told the audience that they are helping train AI! Here's how: you've probably seen reCaptcha (CAPTCHA stands for  Completely Automated Public Turing test to tell Computers and Humans Apart). It asks you to prove you are not a robot by reading and typing some obfuscated letters or to identify things (like street signs) in photos. When you reply, you are actually training AI! Apparently not many are aware that they are helping AI to identify words in old books and helping to train Google's AI visual recognition.
  • Yes, supervised learning AI needs lots of data
  • Note: there is another type of AI called "Reinforcement Learning" where AI does not need lots of data in the same way as Supervised Learning. In layman's terms, it is given a reward/goal that has a value and then it keeps attempting to improve itself to attain that reward. This video shows an example of Google Deepmind teaching how to run and jump. You can find more to "play" with AI on Google's page of experiments.
  • Here is a good article explaining some of the main terms of AI and another one explaining AI, Machine Learning and Deep Learning

AI Bias and Interpretability
  • There is a whole research area of AI to determine how it arrives at its decisions. It's called Interpretability or Explainable AI (XAI). Because bias has been discovered in AI, there is a lot of research going into XAI with many methods being used. This article gives a good overview of AI and Interpretability with good examples.
  • Henry mentioned during the panel discussion that he worked on a large scale enterprise AI project where two data centers were trained with the same data but arrived at different answers. The audience audibly expressed their surprise at this.
  • Mike Moran asked why should this surprise us; people sometimes express different opinions from each other, so why not AI?
Do I need to Learn about AI?
The panel had various views on this. In my opinion, it will depend on the types of projects you want to manage.
  • If you are working on a project that is going to implement AI, then, of course, you would need to understand the tasks involved. As a PM, you can work with your project team to take the objective and decompose it as a WBS.
  • If you want to make yourself marketable, probably many software projects will use AI in the near future, so that's another reason to learn more about AI.
  • For all PMs, your knowledge of AI will need to be about how it can be applied to the work that you do. AI has a high ROI where lots of repetitive work is being done. For project managers, you can easily list the tasks you do that are repetitive. My experience has been that I have had repetitive tasks in communications (reports and notifications), scheduling, risk, and issue management.

A few sentences on AI and Project Management

(This section was contributed by Sandipan Gagopadhyay)

1. AI such as machine learning is good at synthesizing patterns from vast amounts of data. If an organization is using a project management solution (such as MS Project Server) over a few years consistently, then information can be harvested to derive a number of insights:
  • Supervised Learning examples - Prediction of accuracy in time and cost estimation in projects
  • Prediction of issues and their impact based on challenges and risks based on NLP and ML-based review of unstructured RAID logs
  • Unsupervised Learning examples - Classification of high variability when projects involve specific clusters of technology, teams, locations that in turn can shed light on underlying policy or process issues
  • Here's a Forbes article titled "AI in Project Management"

2. AI/ML projects have unique requirements for Project Managers in that the techniques used require modifications to the SDLC, whether in waterfall or Agile

  • AI/ML projects involve precursors including the collection and determination of quality of data that will drive machine learning
  • Key steps to identifying the feasibility of a machine learning solution such as feature identification and selection require an iterative with a fundamentally undetermined outcome and timeframe - This requires prototyping early on before any commitments are made to business or in the delivery of value, financial or otherwise
  • The quality assurance and validation functions require an engaged and a deeper supervisory role in the overall approach to AI rather than testing results at the end
  • Please see FDA's proposed regulatory framework for AI/ML in Medical Devices -
  • Artificial Intelligence and Machine Learning in Software as a Medical Device -
(Sandipan, thanks for that helpful input!)

The Software Development Life Cycle (SDLC) 

There was some discussion among the panelists about how the SDLC is different for AI projects. My experience has been mostly with supervised learning AI. In supervised learning, humans have to tag (or label) lots of data in order to provide training for the AI.
So, I've found that for chatbots (and lots of AI projects), there needs to be a lot of work both in the beginning and after go-live. In the beginning, people need to be involved to identify and analyze data to train the AI. I've also found that many business people believe that AI learns on its own or will teach itself. So, they think that once the AI is live, there will be little effort required. With Supervised Learning, humans have to be involved in analyzing what is happening in user interactions and training/re-training the AI. This needs to happen continually to increase the effectiveness of the AI. So, there is a large amount of effort required even after go-live.

AI and Project Management

The Project Management Institute (PMI) has made available a 4-page report on Project Management and AI. They provide results of a survey of 551 Project Managers. The paper is titled "AI Innovators: Cracking the Code on Project Performance" (2019). A review of the report was done by TechRepublic titled "6 AI technologies changing project management" mentioning 6 AI technologies that are impacting organizations. My takeaways from the article are:
  • Some companies are actively involved in AI and seeing benefits already while others are lagging behind. 
  • The article looks at the principles being used by "AI Innovators" Vs. "AI Laggards".  
  • It mentions that Accenture research found that visionary organizations apply five key principles identified by the acronym MELDS: Mindset, Experimentation, Leadership, Data, and Skills.


With my experience in Natural Language Processing and chatbots (and my knowledge of Machine Learning, Deep Learning, RPA, and predictive analytics), I can see how these AI technologies and others can be used to help Project Managers. I've reviewed several articles (see the reference section below) and agree with many of them mentioning ways that AI can help PM. However, I've not yet found a whole lot of specific information showing how these AI technologies are being applied to help Project Managers.
I do believe that AI will grow in its use, so PMs do need to learn about how to lead projects using it, how it works, what it's benefits are, and how it can be applied to help them.

I would like to hear your comments and questions about this article and your thoughts on AI and project management. Please comment below. Thanks for your time to read this.

All the Best! Have a great day!
Henry Will

Reference: Additional Information on Artificial Intelligence

Sunday, March 22, 2020

Resources for families during COVID-19 Coronavirus

Updated 2020-05-22 12:03 am EDT (new Items in red in many topics below)

Here are resources available for families during this crisis.
  • This blog post will be updated as we find more information
  • please comment below with resources you know of and we'll add them to this list
  • Feel free to share this with others
  • Come back often for updates
Sections below:
  • Other lists of resources for help during this crisis
  •  Virtual visits to Zoos, aquariums, museums, book readings, historic places, beaches, national parks, farms, gardens, how to draw, comedy, games, 
  • online exercise
  • online games
  • Conferencing software
  • Precautions for Covid (including how to shop and clean)
  • New - Reporting information on Covid and Coronavirus
  • for workers and those looking for work
  • For small businesses
  • Information on getting your stimulus payment 
  • Graphics and Communication resources
  • Worship and Spiritual Encouragement
  • Holy week events - many wonderful events available as replays
  • Special events
  • Recipes! 
Please scroll down to see all of these sections listed above.
Other lists of resources:

Resources for Virtual Zoos, Aquariums, museums, sports, space, drawing, book readings, and more
Exercise - many free classes are available
    Online games:

    Conferencing software
    New - Reporting information on Covid and Coronavirus 
    For workers and those looking for work
    Small business information

    Graphics and Communication resources

    Worship and Spiritual Encouragement Online

    Note: many of these are available as replays after being live.

    Special Holy Week events - Most are still available as replays
    Replays and Special events
    Christian resources for families

    Many organizations are providing their recipes during this crisis.
    I'll be adding to this list too!