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
  • Emerj.com : 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

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


Project Management

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" https://www.forbes.com/sites/cognitiveworld/2019/07/30/ai-in-project-management/#74c18a31b4a0

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 - https://www.fda.gov/media/122535/download
  • Artificial Intelligence and Machine Learning in Software as a Medical Device - https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-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.

Conclusion 

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!
Sincerely,
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
    Precautions
    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
    Recipes

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

    Saturday, February 15, 2020

    Productivity, Time and Task Management - 5 tips that have helped me


    Image by Gerd Altmann from Pixabay
     
    I've always been interested in being productive and making the best use of my time.


    I've mentored people about productivity and spoke to people about it too. Back in 2009 I blogged here about Innovation and Productivity.

    I lead a net-working group called Emmaus Work Connectors and last month (January 2020) our discussion was about "Time and Task Management."  I told the attendees that I would share some of the information so everyone can have access to it and benefit from it.

    Here are some things that I've learned over the years that have helped me with links to articles to get more information about each:

    1. Prioritization is important:
    We need to prioritize our work in two ways: importance and urgency. Tasks that are important and urgent need to have the highest priority. The tasks that are important and non-urgent need to be scheduled so we get around to doing them. I first learned about this in Habit 3 of "The 7 Habits of Highly Effective People" by Stephen R. Covey. I've lately heard it attributed to Eisenhower. One pointer from me is "don't over-analyze" prioritization. Get it close and then just get started on a task.

    2. Using a process helps.
    Getting Things Done (GTD), Personal Kanban, Agile Scrum framework (video or .pdf), and the Pomodoro technique are great processes to aid in managing tasks.
       My main take-aways from GTD is that tasks that are less than about 5 minutes are best to just do right away to keep them from getting on a list. And, take any big projects and break them into smaller ones.
       I've used Kanban at work for years. I also follow Personal Kanban for my home tasks. Kanban is the most effective technique that I use. It is based on two easy rules: visualize your work and limit work in progress. I use Trello to visualize my tasks on a kanban board. I use it to track all of my tasks. I find Kanban helpful because by limiting work in progress, it stops me from trying to multi-task which has been proven to be inefficient and even damaging to your brain
       I also find that by using the agile scrum framework of bringing a limited number of tasks from my big "to do list" into a "timeboxed" period of time (one day or one week) keeps me from being overwhelmed by my big list. I believe that agile techniques can be very helpful to apply to my every day tasks. Read a bit about it and see if you agree.

       My take-away on Pomodoro is to concentrate on one task at a time for a certain amount of time. Taking breaks is important too and a part of Pomodoro. I find it refreshing to plan a task that takes about a half-hour, work on it, get it done and cross it off the list. Well, in Kanban, I move it to the "Done" column! In Trello, there is even a way to pop some confetti when you move a task to done! (note: Trello can also be used for Pomodoro as one of the several add-ons covered in this article) and it can be used to implement GTD too!)


    3. Eliminate (or reduce) distractions
    A key part of productivity is to reduce distractions, especially distractions that are unimportant (thinking back to the Eisenhower prioritization mentioned above.  This means you may need to turn off sounds for texts on your smartphone, email and other messenger platforms. Another great productivity framework called Inbox-zero (about processing all of your email so your inbox has zero emails left) tells us to just look at emails a few times a day. All these messages are distractions. Distractions pull us away from focusing and it takes considerable time (23 minutes according to one study) to get back on task.
    Background noise sometimes helps to reduce distractions around you. I've been known to use coffitivity and other similar websites to make some background noise when I'm being distracted. Try it out!


    4. Don't over-analyze, get started on a task
    If a task seems to overwhelming, think of one thing you can do to get started on it. Start that one thing. Usually, this is enough to overcome the feeling of being overwhelmed and gives the feeling of momentum. Try it!

    5. Do tasks with long leadtimes first
    If something is going to take a long time for someone else to do, or to get a response, get that item into the "pipeline" as soon as reasonable so that you won't later be waiting on it.

    Now you try

    These are just a few ideas and this article is already way too long, so I'll stop here. This is enough for you to try.

    I use Trello a lot and they regularly post on the topic of productivity.
    Here's a blog post they did about "Self-Management: How To Prioritize And Be More Productive"  and another titled "How To Create A Productivity Tracker To Reach Your Goals This Year"

    What do you think?
    I would like to hear about your productivity tips. Let me know if any of the above tips helped you or not and why.  Let me know if there are other topics or questions you would like me to cover.







    Saturday, November 16, 2019

    Rise Against Hunger 23,000 meals packaged! You can too!



    On October 26, 2019 about 105 people got together for about 2.5 hours and packed 23,000+ meals with Rise Against Hunger. This picture shows just a portion of the meals packaged.

    We had people packing meals from a net-working group that's hosted at the church, youth group members, boy scouts and cub scouts, the Interact club from the Roxbury High School and other community groups.

    The work started about a year prior to this with many fundraisers to raise 34 cents per meal for a total of more than $7800.
    Fundraisers included asking businesses for contributions, a fundraising dinner (Hillside3d.com), the youth group doing a car wash, bake sales, and more.

    A member also sold more than $20,000 worth of Shoprite gift cards.  ShopRite donates a portion of the sale to the fundraising. If you would like to support our event next year by buying ShopRite gift cards, let us know.

    Printastic donated the banner this year for the event so we could list all of the many supporting organizations. Some of the organizations were Diamond Gymnastics, Joe’s Pizza, Bryan’s Luncheonette, Nordic Contracting, Ronetco Supermarkets (ShopRite), Panera, Haagen Dazs, Flanders Bagel, and Fuddruckers. Please visit our supoorters.

    Thank you to the many people and organizations who gave of their time to raise funds and pack meals.

    Thank you to the many businesses, organizations, and individuals who supported the fundraising.

    This year’s event was a follow-up to last year's event and we plan to do it again next year on Saturday, October 24, 2020. Here's where you can find out more, donate, or sign up to help.



    Tuesday, October 29, 2019

    A New Type of Net-Working Group

    Image by TeroVesalainen from Pixabay


    We've started a new type of net-working group.

    It's Net-working because it's people who are working and people looking for work who are getting together to work on their "work journey". They help each other and work on the topics they choose together.

    It's a group meeting monthly (Third Thursday) face-to-face in Morris Country New Jersey to discuss what they've applied. (Yes, we're in discussions about adding a monthly virtual meeting too).

    It's also small teams (within the bigger group) of people meeting virtually every week or two (at an agreed time) to work together to apply tasks to make progress on their work journey.

    It's also finding a "buddy" in the group to meet with a few times a week (phone or in-person as they agree) to help each other make progress on their work journey.

    It's for people working and for people looking for work. Why? Because they can help each other since they have experience in the work journey.

    It's about working together to build strong connections with others; this is the best form of networking.

    We also take into consideration that the work journey is a spiritual one, so we address the spiritual needs too.


    Come join us. Read more and sign up at this link


    We are currently meeting in Morris County, New Jersey. As the group grows, we are considering expanding to other locations and virtual meetings too.

    Sunday, March 31, 2019

    Digital Transformation and Disruption


    Image by geralt on pixabay

    Someone was asking me today what my definition of Digital Transformation is. My definition is below. I had to think about it because I will be doing a presentation on the topic of "Managing Digitial Transformation and Disruption" on May 6, 2019 at the PMI NJ Symposium and I will provide the audience with a link to this blog post so they can find more information. So, this blog post will most likely be updated over time.

    My Definition of Digital Transformation:
    Digital Transformation is the use of digital technologies (AI, IoT, Cloud, Big data and analytics, blockchain, AR, VR, drones, etc.) to transform business.

    It's not just about changing existing systems to use these technologies, but it's about leveraging these technologies to transform business.

    Digital Transformation is much more effective when it delivers a focus on the customer.  There are several links below that demonstrate that importance.



    Some helpful links:

    Digital Transformation (DT) Definitions
    Digital Transformation Articles
    Digital Transformation Pitfalls and Fixes

    Digital Transformation and Project Management

    Digitial Transformation Use Cases

    Disruption / VUCA (Volatility, Uncertainty, Complexity, Ambiguity)
    Artificial Inteligence:

    Customer Experience and Design Thinking

    • The Right Way to Lead Design Thinking - Harvard Business Review March-April 2019. This article speaks about the importance of empathizing with the customer. There are good case history stories and a good example of how to navigate ambiguity.
    Project Complexity (occurs during DT)
    • Project Complexity Model - This article explains many aspects of project complexity. Most, if not all of these, occur in DT projects