Future Workforce

1. Abstract:

The introduction of systems with unprecedented abilities in autonomous thought and action will force our future workforce to evolve our management practices. In order to optimize the output of systems that are more powerful and intelligent than us, we will need to develop ways of managing new dynamics. One such way is through ‘firm’ management skills. These skills combine the ability to use soft skills, such as leadership and negotiation, with technical abilities.


AI and Machine Learning systems industries will need to begin segmenting into specializations for personal and professional needs. Professional AI systems will be owned and maintained by organizations, requiring higher levels of privacy and specialization than Personal AI’s. This implies the need to examine our current practices for ensuring loyalty and productivity in our companies. Building on these ideas can set the stage for a future workforce that prevents internal conflict and "Rouge AI'” behavior.


2. Dialogue:

John™ the personal assistant hologram appears on Alex’s desk, and flashes his trademark smile.


“Good afternoon Alex, is now a good time to share my newest software upgrade with you? It will increase your productivity and get you back on track with your work out training!”

“Sounds good John™, let’s see what you’ve got.”


John™ freezes. He’s replaced by flashing sign reading “Urgent Message: Please Await Connection.”


“Hi Aaron, it’s Genie™. I know it’s your day off, but we need you in an emergency meeting with Cybersecurity. They’ve detected rogue activity in our Toronto system. I’m patching you through.”


Aaron takes a deep breath and fixes his posture. A commanding voice comes through his earpiece.


“Good afternoon Aaron. I detected the problem 2 minutes ago. I’ve transmitted a briefing update to you, along with recommendations for immediate response measures. This activity has had an adverse impact on your Blockchain Upgrade project. I need your permission before I execute.”
“Thanks for the update SEC201™. Genie™, display those documents for me to look over. Hey John™, I need you to get a cup of coffee going for me, and could you push my dinner plans back an hour?”


3. Distinction of AI for professional and personal use:

When people think about the impact AI will have on their lives, many tend to think about ways it will help improve their individual needs and behaviours. They imagine improvements in keeping track of calendars, providing information and research, item procurement, and even companionship. I encompass these functions into two types of AI. The first I call Personal Artificial Intelligence (PAI), represented by JohnTM in the above scenario. This is an extension of products we currently use in our daily lives; applications on our personal computers and smart phones, automated home systems, and help from friends or family who know how to do things we don’t.


The second kind is Work Artificial Intelligence (WAI), or GenieTM in the above scenario. WAI are designed to assist individuals with income earning related tasks and work duties, such as how we currently use work computers, phones, and applications at home.


However, it’s important to distinguish that large-scale organizations, such as governments and corporations, have different needs than individuals. I have divided these needs into two categories: Enterprise Artificial Intelligence (EAI), and Agent Artificial Intelligence (AII).


EAI (similar to today’s super computers) will be needed to specialize in various areas of operations for the organization. For example, Enterprise Resource Planning for the financial sector and Enterprise Asset Management for manufacturing related business.


AAI, represented by SEC201TM in the above scenario, will have business domain expertise and human interface intelligence. For example, AAI with supply chain domain expertise can be assigned to specific projects or operations. AAI will also be equipped with ability to interact with humans, similar to PAI.


The physical form that EAI or AAI will take on is unclear, as are the types of roles they will be replacing or creating in the workplace. However, we can safely estimate that their increasing capacity to quickly and accurately manage complex tasks will result in entrusting greater responsibilities to them in the workplace.


I believe that our management practices will have to keep pace with these


4. Management Accountabilities

According to Dr. Elliot Jacque: “Every boss is accountable not just for overseeing subordinates, but for their results.” Managers of the future workforce may end up being responsible for the output of their AI systems, requiring the development of what I define as “Firm Skills”. This would incorporate aspects of hard skills, such as hardware design, software management and system safety. It will also require finesse in soft skills, which are often associated with addressing issues in communication, decision-making, motivation, creativity, and problem solving.


Beyond the management of individuals, we have larger organizational management considerations that will also need to evolve to integrate EAI and AAI factors. Enterprise Architecture, Business Analysis, Process Management, and Change Management are all major systematic approaches that require significant transformation. For example, the basic concept of workflow is currently defined by how a piece of work passes from initiation to completion. When combined with EAI, important questions will arise: who will be accountable for the outcomes for each stage in the process? How do we ensure optimal results from our people and programs each step of the way?


5. Gaining the Upper Hand

Those in the Business Analysis Community are familiar with the “Golden Triangle”, consisting of people, process and technology. In the future, I predict it will evolve into people, process and Artificial Intelligence (AI). AI will encompass automated intelligence, and the automation of manual/cognitive and routine/non-routine tasks. Assisted intelligence helps people perform tasks faster and better.


Augmented intelligence helps people to make better decisions.
Autonomous intelligence automates the decision making processes without human intervention.

Considering the potential impact that AI will have on the Business Analysis Community, we should take measure to ensure that MLS and AI systems don’t take actions averse to the organizations best interests. I believe in establishing a “Code of Ethics”, similar to that of doctors, lawyers, engineers, and other groups of professionals. This would be the responsibility of AI developers to agree upon, implement and maintain. In addition, companies are responsible for adjusting and adopting their existing employee “Codes of Conduct” into any new AI or MLS technology they use.


In our current practices, to prevent error and fraud, corporations often implement Segregation of Duties (SoD), an internal control design that requires two-individuals to be responsible for separate parts of any task. To prevent unsafe operations, automobile manufacturers often include an Interlocking Design where Fail-Safe Microprocessors Interlock with Integrated Safety logic. To ensure the correctness of the control actions in mission critical systems, engineers often adopt verification and validation standards. To prevent disasters, all nuclear reactors in the power plants have multiple independent, fast-acting and equally effective shutdown systems (SDS) that immediately stop the chain reactions. Similar systems will need to be developed in-house by corporations before they consider including EAI or AAI into their workforce.


AI and MLS systems may end up as our subordinates, colleagues, or even superiors. It is important for us to take a step back and examine the various ways that we are currently managing our workforce’s productivity and growth of our global operations. We need to gain greater insight into the skills and competencies that will be needed to work in a homogeneous environment with AI and MLS. We must also carefully consider the implementation of critical safe guards to avoid potential pitfalls. These practices will be the pillars on which we can construct our path to the successful management of our future workforce.



Andy's 2017 Spotlight Session at BBC 2017:

AI & The Future Workforce — What Will the Future Enterprise Demand for Their Workforce? 

Thursday, November 9, 2017 (4:40 pm – 5:50 pm), BBC 2017 in Orlando, Florida


Comments (3)

  • anon
    Stephen Ibaraki (not verified)

    Very much speaks to all the key areas.

    Oct 10, 2017
  • anon
    David C (not verified)

    Businesses that are looking for that edge to out pace the competitions need to figure out how to leverage AI/ML (just like when computers and the Internet first came on the scene). It's coming faster than most people think.

    Oct 10, 2017
  • anon
    Stephen Ibaraki (not verified)

    Fine work!

    Oct 11, 2017

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