AI technologies are not new. They only became popular after some time. They have been around for decades.  As a result of supporting components such as cloud architecture and semiconductor chips, using AI technologies has become more accessible. This accessibility brings this topic into the mainstream for discussing positive and negative impacts.  

Aruna Pattam,  Head of AI & Analytics for the Asia Pacific region, is my guest on this episode.  In 2021, she was Linked in Top Voice 2021 for Technology and Innovation and recently named of the 2023 Top 100 Brilliant Women in AI Ethics. Additionally, she continuously contributes her thought leadership as a group member of the Responsible AI Think Tank. 

 In Jan 2023, Aruna published her perspectives on the Top AI Trends for 2023. Today's discussion discusses those trends and why we should be watching these more closely in 2023.  1. Impact of AI and Cybersecurity 2. Democrationalization of AI 3. Edge AI 4. Generative AI 5. Responsible AI

This interview, our discussion, and our views are now a part of the global data set.   

According to Laura, data is impartial. It doesn't have human-like qualities. The unclean data, the unstructured data is the best mirror to ourselves. Ultimately, we are responsible for the data-sets that are pulled into other organizations. i.e. we buy, we post, we upload, we like, we repost. 

We can clean data to redefine a better 'prettier' answer,  but if we want to fix the data, we may want to shift that focus to ourselves.   "... you play an active role whether you have known it or not. You have been in it all along", Laura.  "We focus on all the things that can go wrong (when discussing AI technologies), but there are benefits that can be used for good with the right gaurd rails. We have to sift through the not good in order to acheive the good", Laura.   

Additional Topics Discussed:  - Definition of ethics - Applying ethic concepts to AI technologies  - What does it mean to be a human in today's world - Moral decisions and consequences - Bias exists comes from us, the human interaction - Broken mirror theory, Laura's theory based on years or observation and reflection - AI algorithms are not entirely responsible for all the bias themes - Ethics look at the harm when the result provide the wrong answer that is harmful - Ethics-washing - we always want the pretty version without the work - Books: How to Lie with Statistics & Merchants of Doubt - Transparency Fact Sheet - Are we missing anything? - Regulations are written after innovation, i.e. Copyright Act, written in 1976 - Policies.The future requires dedicated resources to revise policies on demand or every quarter. - Right, good, fair, and just - Laura' answers the question, 'what can someone do to start thinking differently about ethics, that impacts us personally' - Protecting your images, what your have contributed yourself you may not have thought much about until now  

https://www.linkedin.com/in/lmiller-ethicist/

AI-related projects are not typical IT projects with a traditional waterfall approach.  My conversation with Lisa Palmer, Chief AI Strategist & Ethicist, AI Leaders focused around her recent doctorial thesis and research on 'Artifical Intelligence: Are For-Profit Entities using the "Do the right thing' goverance to drive business results"  

When her customers claimed they were 'doing the right thing', Lisa wanted to take that further i.e. 'What does that really mean and more importantly, what does the customer believe that means?  This led to her doctoratal statement and how companies are: 

 1. Making decisions 

2. Taking action 

3. The results of those actions  

AI Technologies are still reletatively new in how they are being used in for-profit entities. She turned to podcasts to collect the foundational data related to her thesis statements for recent and relevant information. Listening to 172 podcast episodes and narrowing this down to 46 specific scenarios included in her study, covering a date range from the last 3 years up to April 2022.   

There are 3 ways AI technologies are being used in enterprise companies: 

1. Efficiency of processes 

2. Revenue opportunities 

3. Risk Avoidance  

Other questions discussed during this episode:  -Self-adopted policies - What are companies actually doing from a policy perspective? -What are the types of companies which are doing this well? -Is the AI champion a benefit to the enterprise organization, or are there unintended consequences -What about companies that are focused too broadly? -What is a reoccurring theme for successful companies? -How important is the quality of diversity in viewpoints or successful companies? -How influential is company culture when executing AI-related technologies? -Can AI policy and regulation restrict our ability to innovate?  -Is there a disadvantage to the US which is not writing AI-related policies and regulations but instead -This remains a fluid topic. What do we need to address in 2022-2023?

A recent graduate from Nichols College in Boston, MA and now working as an Automation Engineer at Paragus IT, Skyla started her educational journey with an Accounting degree,  but later changed that concentration to technology and automation.   

In a conversation with her advisor, it was suggested perhaps Accounting wasn't the right fit. These discussions led to an internship through Center of Intelligent Automation (CIPA) program at Nichols College.  Skyla defines automation as the improvement of manual processes that are rule based and repetitive. Mostly data entry that was occuring daily or weekly. She using Power Automate with Microsoft to support her automation  Two (2) examples where she has made a visible impact to her internal stakeholders are:     

- The same email is sent every week, from the same supervisor with the same body of content to remind folks about their time sheet.     

- Employees submit reimbursement requests via paper. Through the use of mobile app, employees can send those request very quickly and can managers can quickly approve or deny.  

Other topics discussed wtih Skyla:  

- What prompted the change - the appeal and challenge - Types of activities as an automation engineer - Not every process can be solved by automation.  - Do stakeholders reach out to the department or is it a struggle for internal stakeholders to embrace automation? - Listening is the #1 skill set. The process is explained differently by different people or doesn't exist on paper. - The value of current state processes - Skyla's recommendations for other women just starting their career journey.  https://www.linkedin.com/in/skyla-w/ https://www.linkedin.com/company/paragus-it/

AI4Good. We talk about this often but haven't focused a lot of time on understanding the 'good' part of this phrase. It is women like Shiran Somech who are using AI technologies that truly have a global social impact.   She has found the perfect blend of her two (2) primary passions of AI technologies and wants to make a visible social impact on women's rights. Our discussion talks about her initial idea and carrying that forward from concept to reality, leveraging AI Technologies to create something that may not have been possible five (5) years ago.   

Social Media Campaign 'Listen to my Voice' An AI-based campaign speaking up against domestic violence uses AI technologies to bring the voices of women murdered by their initimate partners who are no longer here to tell us their stories.   Our conversation covers the partnerships, the impact, and some technology challenges she had overcome in bringing this campaign to life.  This could not have been possible without the support of the families. To realize this concept, collaborate with non-profit government partners, tech creators, and sponsors. As a result of its extraordinary success, the campaign is now being duplicated around the world: https://www.listentoourvoices.co/en/. 

Volunteer Special Projects Tochnit Saleet, is a program sponsored by the Ministry of Welfare & Tel Aviv Municipality to help women break out of the sex-work cycle and integrate into the hi-tech workforce. In this role, Shiran helps to raise funds, provide mentorships, and upskill women, enabling them to enter the Israeli technology market.

"Best Friends is transforming the animal welfare industry and data is transforming Best Friends", Michelle Dunivan, PhD Dunivan, Analytics Director of Best Friends Animal Society.  As we approach the 2022 holidays in the United States, the adoption of kittens & puppies increases as gifts to family members.  

What we don't see is everything behind the scenes to ensure your local animal shelter or rescue center has the right balance of animals to service local demand. We never see the amount of data which needs to be collected,  to resolve key business challenges for the betterment of animal welfare. 

In talking with Michelle, data provides her organization with the ablilty to ask questions no one thought to consider five (5) years ago because the data wasn't as accessible as it is now.  In the future, data can help Animal Welfare Industry to be proactive instead of reactive to really understand the pyschology of adoptions.  

What if data could help us understand (or predict) the outcome when a type of dog breed is accepted by the local shelter in a geographical area, at a certain time of year, and possibly the time of month.  

We packed a lot information in just under 30 minutes. Other topics during our discussion include:   - Roles & reponsibilities supporting data and analytics in animal welfare  - Research in the real world compared to the obstacles of academia research  - Studies: Animal Behavior (kpeeing animals living longer)  - Research: Community cat programs  - Supply and Demand: what animals are needed in which states  - Myths: Pandemic Puppies are bring returned. The data refutes this perception  - Data collection: Collecting from animal shelters across the United States  - Establishing the right amount of data to achieve our business goals   - Reporting to bring actionable decisions not just to have lots of data  - Constituents, volunteers, donnations, and local state and county policies

"There is no such thing as a bad project, only poor project planning." Personally, this has been my quote for 15+ years. Executing a good project plan is a balance between decisions and data. The decisions we make before and during the project and data availability facilitate those decisions.  

We have all been there. Using XLS instead of Microsoft Project to create a project plan with just enough detail to allow you to track the progress, and yet somehow, we cannot make accurate decisions with a high level of confidence about the success or failure of the project. Yes, we can say the project is ahead or behind, and we know when a project goes longer than expected, we can use the existing run rate of our resources to estimate how much more money will be needed to finish the project.  

What about the majority of projects that continue to go over budget or run long multiple times before the project is completed?  How do we know when and where to shift resources to other workstreams, so the project is back on track?  More importantly, can we predict a project will be successful or fail before the kick-off and explain why?  

With the accessability of AI technologies, Greyfly.ai combines the foundational concepts of project management to generate true project intelligence. This software solution enables project managers to predict proactively the expected success or failure of a project and, during the project, outline what project parameters need to be changed to bring the project back on track.   

In talking with Marcia Williams, Chief Product Officer of Grefly, leveraging AI technologies on top of the data enables predictive analytics to address project questions with higher confidence. The fact-based decisions reduce the risk that can drive potential savings (or cost-avoidance. The historical data can be used to highlight if a project has the potential to be a failure and address the 'why.'  

There is a US cartoon in the 1980s I used to watch on Saturday mornings called  GIJoe. Their slogan was 'knowledge is power and 'knowing is half the battle. With improved project intelligence, using AI technologies is helping to harness the power of project data and to answer the one question we could not figure out before 'Why?'.  

Other Topics Discussed:   

- a professional journey from IT auditor to Product Development 

- data quality -

- drive a fluid business culture to allow the customer to take you where you need to go 

- the product officer's role 

 - resource capacity through an organic growth structure

According to a World Economic Forum study, it would take 152 years to close the gender gap if we did nothing more than what we do today. 

This was just one insight during my discussion with Debbie Botha, Global Chief Partnership Officer, who further describes the Women in AI organization as a 'Do-Tank', not just another 'Think-Tank. 

"Even with the hardest efforts, we will still be biased human beings ....it is important teams build the future of our world with AI applications to embrace internal diversity as much as possible to create an inclusive AI and represent a right image of a multicultural society. That’s why we need... more women in AI, but (also) more diversity in general. This can extend to skin color, religion, education, country, family, age, etc.," Founders of Women in AI 

Started from a grassroots organization, Women in AI has grown into a global organization in 150 countries with boots on the ground in over 40 countries.  

Our conversations dive deeper into the following:  

 - making a visible impact on minimizing bias and closing the gender gap  

- five (5) ways to increase (or speed up) the process 

 - how does culture impact, hurts, or help the progress  

- example such as job description, where a small change can make a big difference

Is customer service really servicing the customer if the priority is capturing data rather than understanding the customer?  

Think about the last time you called customer service and spoke with someone who spent more time on data entry than really helping you, or what about a non-profit organization whose support center is manned by volunteers or interns?  Perhaps the customer service agent does not want to ask the customer to repeat themselves and thereby miss out on documenting key information, or perhaps the agent is so busy hearing the conversation for data entry and not listening to the customer's needs.   

Wyser is a 2-year-old start-up using AI technologies to document, in real-time, the voice of the customer. This reduces data entry errors while increasing data accuracy. More importantly, it allows the customer service agent to provide service to the customer rather than risk escalating customer frustration even further.   

Donna, "we are processing data in the most intelligent way to fully use it without someone having to manually look at it.... able to identify patterns and keywords to establish trends and then adapt accordingly."   

Additional topics discussed are:  

 - Shifting into an early-stage start-up from a long career in the industry 

 - Is this value of what you are doing immediately understood 

 - Types of bias in the traditional customer service approach 

 - Cultural challenges in off-shore call centers 

 - Loss of valuable information due to individuals who are slow at data entry

TBDWith the increase of AI technologies and, at the same time, a decrease in the cost of using those technologies, we are seeing a rise in startups and small businesses that can focus attention on solving specific business challenges.   

In this episode, Erin McFarlane, VP of Product Innovation at the Boston, MA startup Fairmarkit is doing just that with a new round of funding in 2022, bringing 'fairness to the market is possible.  Three (3) years ago, Erin took a risk to shift from working on the buy-side, most of her professional career, to the supply side and work with a very young start-up company.   

Erin, "Policies often state using procurement at a threshold of $X. P-card is reserved for smaller but more frequent spending. The middle ground is where Fairmarkit excels, supporting both direct & indirect spending."  

Additional topics covered: - What lured you away from industry to a start-up? - Fairmarket overview - What use cases is Fairmarkit solving for? - Does it really cost more for the organization to use diverse suppliers? - What and where are the AI technologies used? - Lessons Learned in working with Startups from Erin