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Alain Thiry

Building Customer Loyalty

Alan Shoebridge is senior director of marketing operations for Providence Health & Services, an integrated health system that includes 34 hospitals, 475 physician clinics, and many other health and educational services. The third largest nonprofit health system in the United States, Providence employs more than 76,000 people across Alaska, California, Montana, Oregon, and Washington.  Alan has more than 15 years of direct marketing and communications experience for healthcare and medical insurance organizations with a focus on marketing plan development, advertising, messaging, research, and other areas. He has also worked as a newspaper reporter and in public relations. Alan earned his BA in English from the University of Oregon.

Alan Shoebridge

Alan Balutis is a distinguished fellow and director in the North American Public Sector Consulting, Internet Business Solutions Group, of Cisco Systems. Mr. Balutis has served in public-service and industry leadership roles for more than thirty years, as president and chief executive officer for government strategies with INPUT, a leading market research firm, as chief operating officer  of a small, minority-owned firm, and as a leader of the Industry Advisory Council and its parent group, the American Council for Technology. During his twenty-seven years in the federal sector, he was the first chief information officer and head of the Management and Budget Office at the Department of Commerce and also served at the Department of Health, Education, and Welfare. Mr. Balutis is a founding member of the Federal Chief Information Officers Council, where he led strategic planning and outreach committees. He is a five-time Federal Computer Week FED 100 winner and a member of the Government Computer News and Federal Computer Week halls of fame. He is also a fellow of the National Academy of Public Administration.

Alan Balutis

In January, OpenAI’s conversational platform, ChatGPT-3, became the fastest-growing app in internet history. This is just one indication of growing curiosity about GPT (generative pre-trained transformer) and other chatbots in the past few weeks. As one of the first learning professionals to see the potential of conversational AI and one of the few designing the applications for years, I’m excited to see the recent attention paid to this engaging technology.In my book, AI in Talent Development, I outline several ways chatbots can be used as part of a robust learning experience, and ChatGPT-3, the third version in OpenAI’s ChatGPT series, demonstrates most of them. When ATD asked me to write a post on this subject, I struggled to find the value I could add to the exploding conversation. I decided to do what people say I do best: Give you the bottom line and point the way towards practical applications. Let’s start with the basics.How ChatGPT-3 WorksChatGPT operates on an autoregressive model. It’s not as complicated as it may sound. A transformer is a program, model, or algorithm that converts code into something else—in this case, human language. The autoregressive part means the software uses prior events to predict the most likely future events, which is what your brain does all the time. It allows ChatGPT and similar applications to simulate a conversation between two humans. Learn the two keys to making an application like this work:1. Natural Language ProgrammingNatural Language Processing (NLP) allows the bot to recognize input through human speech or writing, eliminating the need for menus or code to engage with it. This same ability enables the bot to reply through text. Before the development of NLP, most chatbots were menu-driven, and the bot responded by selecting the best fit from a database of pre-written options. Conversational AI represents a new way for humans to use computers; it’s a user interface requiring less hardware and prior knowledge than any previous UIs.!CAUTION! Don’t confuse Natural Language Processing with the pseudo-science term using the same acronym. Neural Linguistic Programming is widely disproved and an invalid practice.2. Massive Training DatasetsLike any neural network (including your own), AI models must be effectively trained using a technique called deep learning. Quite frankly, the stunning capabilities of ChatGPT-3 are nothing new. As David Chalmers points out, there is no new technology here. There are many bots with similar abilities, and I described them in detail in 2020. How this bot is trained and how well this approach works is innovative. First, Open AI used the largest training dataset, combining a database containing much of the internet, a huge library of books, and Wikipedia.Then, after refining the bot in-house, Open AI released it free to the world. As we all started to play with it, we were training it further for them. Think of it as a crowd-sourced training effort. The sheer size of the training database resulted in what everyone always expected: Impressive results that can mimic human expression so well it is hard to tell a machine generated it. However, there continues to be an underlying problem: Chatbots are only as good as their training (like us humans). If you consider the source of GPT’s training, you can see why it sometimes makes mistakes.What Can We Do With ChatGPT-3?Because this product is still being explored, there may be new use cases by the time this post publishes. Below are a few applications that can save time and make your work as a learning professional more efficient and productive.Write ContentIf you ask the bot to write a paragraph introducing a subject, it comes back almost instantly with plausible, grammatically correct text. Because its training included unvalidated sources like the internet and Wikipedia, some of the content it produces must be corrected. Still, you can get excellent first drafts and refine your content from there.Summarize DocumentsLooking for a “Reader’s Digest” version of a book or article? Paste the text into a prompt to ChatGPT, and it returns a nice summary that should hit most of the highlights.Write and Troubleshoot Computer CodeBecause ChatGPT was built to analyze and produce output in human language, it is also great at computer languages. Programmers are using it to troubleshoot code. It can even generate new code if you ask it to develop a new capability.Translate DocumentsFar more effective than other translators out there, ChatGPT can take a website or article and translate it into another language.Write and Grade QuizzesYou can feed your content into GPT and ask it to generate a quiz with answers. Or, give it a general subject, like world history, and it will do the same. Feed your student’s quiz responses into GPT, and it will grade them (even essays!).Create GamesI asked GPT to create a game teaching sixth-grade students about the solar system, and the bot came back with a fun adventure through space.Improve Your WritingI didn’t do this for this article, but I could have asked GPT to review my draft and suggest improvements.Conduct ResearchI asked the bot to provide a list of current peer-reviewed studies on chatbot use in education using APA style and received a properly formatted list.Why Does ChatGPT Have Some People Worried?While most of the comments about GPT are positive, you will find a few educators deeply concerned about this new tool’s capabilities.Mimicking Human WritingTeachers are worried about GPT’s ability to write plausible text reading like a human created it and write in a known author’s style. A student could ask the bot to write a paper in the same style as one of their previous works, and it would be hard to tell the GPT paper wasn’t an original student effort. But, again, this mimicking ability is nothing new. AI has generated art in the style of great artists for years. ChatGPT applies the same predictive approach to language.ChatGPT Makes MistakesAnother concern is the bot’s ability to present false information so convincingly that some users forget to validate the response with research. For example, I asked the bot to calculate the mean of five numbers, and the result was interesting. I received a detailed explanation of the statistical definition of “mean” and how to calculate it, which I did NOT request. However, the bot added the five numbers incorrectly.To be fair, ChatGPT wasn’t built to perform math problems. But it didn’t tell me that or report the result might be incorrect. Like any willing assistant, it did its best to provide an answer. If I had been a student relying on GPT’s help, I would have been wrong. The reason for most of these mistakes is the same reason that it is such a stunning improvement in the chatbot experience: It’s primary sources of information are the internet and Wikipedia.I asked Vince Han, one of the pioneers in building chatbots for learning, to sum up the challenges presented by GPT’s new capabilities, and here’s his response:“One of the effects of ChatGPT & increased quality in Artificial Intelligence in general is shifting the skills users need. For example, most users have developed a skill for how to search which is knowing how to craft keywords and how to sift through search results. Now, people will need the skill of discernment, or learning how to decipher truth and views from a chatbot that provides what reads like a definitive answer. So, from a performance support perspective, yes, one can now get an immediate response to a question but how accurate and relevant that response is will be up to them to determine. “As educators, we must now confront a problem that has been boiling for decades—the decline in critical thinking across most domains, demographics, and workgroups. In my opinion, ChatGPT makes this gap more visible and increases the urgency for closing it quickly.Closing ThoughtsBecause Microsoft owns the license for the exclusive use of the model, we’ve all been working for them, revealing exciting use cases that may find their way into AI-enabled Microsoft products. For now, the platform consists of both free and professional versions. It’s an excellent way to begin learning about the promise of AI and our place alongside it. As machine learning expert Santiago Pino says, “AI will not replace you. A person using AI will.”Where Can You Learn More?There are so many articles about this subject right now that I’ve limited myself to a few favorites:Under the Hood of Chat GPT With Myra RoldanHow ChatGPT3 Impacts the Future of L&D in an AI WorldChatGPT Has Educators Scrambling to Keep UpWhat Is ChatGPT and How to Teach With ItWhat Is ChatGPT and Why Does It Matter?What Is ChatGPT? Is It the Beginning of the End?Ger’s Learning Notes #51 - ChatGPTFor more information and resources, Check out ATD's AI Resource page.

ChatGPT-3 Has Everyone Talking

Until now, there hasn’t been much research on the effect of employees’ feelings on such workplace outcomes as engagement, productivity, or attrition. According to the U.S. Department of Labor Statistics, there is a record low in productivity. And, according to the U.S. Government Accountability Office, the contingent workforce is growing to nearly one-third of the nation’s workforce. On top of this, for the first time, we have five generations of employees working together. If you think fancy foosball and ping pong tables, napping pods, friendships, and golden parachutes will help you become the best and most loved workplace, think again.
The way to become a truly extraordinary company that is loved by your employees and attractive to candidates is by fostering employees’ emotional connectedness to your company. Presenter Louis Carter’s team at Best Practice Institute has proven that emotional connectedness is the strongest self-reported indicator of retention and productivity. The key to becoming loved is creating a culture of psychological safety, consistent positive messaging and communication, and effective group dynamics.
Join us for this webcast and to learn about this exciting new research. You will learn:

what the “best lists” don’t measure and why they need to change
what workplace connectedness is, and how it affects company outcomes such as attrition and productivity
how increasing positive interactions, endorsement, and focusing on future advice can shift thinking
steps you can take to create a culture of psychological safety and emotional connectedness.
 


Increase Performance and Productivity With Emotional Connectedness

As the third largest not-for-profit health system in the United States, Providence Health & Services places great emphasis on service marketing and development. The organization devotes large amounts of time and effort to engage physicians and get the kind of input it needs to communicate with patients in a meaningful way while measuring how effective the services it markets really are. From using online research to determine what patients really want, to identifying operational barriers to cultural change, Providence uses a detailed approach to figure out how to make the organization more attractive to providers and patients alike. This webinar will explore the ways Providence uses research, training, and collaboration to develop effective marketing plans, service promotion, and messaging.

Using Research and Training to Deliver the Services Patients Really Want

The winter 2011 issue of The Public Manager kicks off with a 3-article forum on homeless in the U.S. and what government can do to make a difference. Having had first-hand experience on these matters during my long government career - including assignments with the U.S. Office of Economic Opportunity (OEO) during the early years of the 'war on poverty" and the US Department of Health, Education & Welfare/Health & Human Services (HEW/HHS) - I was interested to learn what 's different in 2012! Well, these articles indicate that today's solutions are largely built around a combination of: 1) sustained, creative intra- and inter-governmental collaboration, 2) vigilant performance measurement (at all levels) and 3) smarter governance.The first article, contributed by U.S Department of Housing & Urban development (HUD) Secretary Shaun Donovan, is "Ending Homelessness in Our Time: Why Smart Government is Key," offers a very promising overview - particularly the "teasers" about actual case illustrations across the country. One would like to learn more about the innovative efforts already showing results in Cleveland, Chicago, NYC, Greater KC, Nashville and the State of Utah and such related apporaches as "HUDstat" and the varied HUD partnerhsips with HHS, the US Departments of Labor (DOL), Education (EDUC) and Veterans Affairs (VA). Are there Web sites where we can learn more about these innovations AND their measurable performance outcomes? I guess for that, we'll have to dig further at HUD's Web site - which I will do and report back in my next post.The second article, Interagency Collaboration Moves the U.S. Closer to Ending Homelessness authored by Barbara Poppe, executive director of the US Interagency Council on Homelessness, drills down more deeply into the strategic planning, goals, roadmap building AND numerical measures of success that have gone into these efforts. The key to all these multi-farious investments and undertakings at different levels of government and the private sector is Opening Doors Across America, "the nation's first (integrated) strategic plan to prevent and end homelessness" which has four goals: 1) ending chronic homelessness by 2015; 2) preventing & ending homelessness among veterans by 2015; 3) preveneting & ending homelssness for families, youth & children by 2020; and 4) setting a path to end all types of homelessness.Finally, in the third article, Homes Wiped Away by Natural Disasters, Frances Edwards, former emergency preparedness director for San Jose CA, shares poignant lessons from several natural disaster-devestated communities that demonstrate what kind of mitigation steps can be put in place to reduce the extent of homelessness. Some of these measure include: risk-based zoning, strict building codes, limitations on building in flood zones and along fault lines, further requirements in wild land and urban interface zones, etc. Again, further probing needs to be done to share links to sites that provide readers with more details on the rich case illustrations Ms. Edwards refers to (including the Whittier Narrows earthquake of 1987, the Loma Prieta earthquake of 1989, the Oakland-Berkely Hilss firestorm of 1991 and Hurricane Katrina less than six years ago.Please feel free to share more thoghts and details (including links) on these and related matters. I will do likewise.

Confronting the Challenge of American Homelessness in the 21st Century

Summer 2014 - The Public Manager

This is the third and most recent book about plain language by Judith Gillespie Myers, a journalist, radio newscaster, and news editor who also teaches government employees how to improve their writing skills.

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