Career at the University of Washington

I started working at the UW as a student in 1968. As a student employee, I provided programming and statistical support to the faculty. After graduating with a M.A. degree in Business, I was hired by Dean Kermit Hanson to create a computing facility for the Business School.

In 1974, the Business School acquired an HP 2000 time-sharing system for instructional support. This was the first interactive system on campus, and aside from the Computer Science group, the Business School was the only academic unit on campus to have its own dedicated computer for student use. The HP system was replaced with a DEC VAX system as time went by and in the early 1980's we started installing IBM PCs.

I started part-time teaching in 1978 and continued teaching and managing the computer resources until 1983 when I resigned my management job and took on teaching as my full-time activity. During the 1980's and early 1990's, the IS curriculum evolved into what we see today.

I had the pleasure to work with undergraduate, MBA, and executive students. I was fortunate to be recognized with student-voted awards at all three levels. After I retired in 2002, the Information Systems and Operations Management faculty voted to award me with an emeritus position.

Artificial Intelligence

Recent advancements in artificial intelligence (AI) have brought the technology to the attention of everyone. ChatGPT has exposed millions to the world of Generative Pre-trained Transformers (GPT) in a way that has shocked even those scientists who work in the field.

Businesses are spending significant energy and resources to see how these evolving technologies can improve their operations as well as provide enhanced value to their customers.

The following set of links provides you with a look at the technology and a sense of its importance.

• Advantages and Disadvantages of Artificial Intelligence
• Top 5 Most Pressing Artificial Intelligence Challenges in 2023
• Escalating concerns for AI in 2023 and what can be done
• The risks of AI are real but manageable

Privacy and Security

With advances in technology, more and more data are being collected and stored by profit and non-profit entities. Much of this data includes personal information on customers and consumers. Entities have an obligation to store, protect and use this information in an ethical and increasingly strict legal manner.

Data privacy revolves around whether or how data are shared with third parties and how data are legally or ethically collected or stored.

Data protection is at the heart of ensuring privacy. So, data security must be a high priority.

The following set of links provide an overview of today’s privacy and security issues and concerns:

• Data Privacy Guide: Definitions, Explanations and Legislation
• What Online Privacy Is and Why It's Important
• Why is Online Privacy Important?
• The Ultimate Guide to Online Privacy and Security
• What is Cyber Security? Definition and Best Practices
• Protect Your Online Privacy With These 7 Crucial Tips
• What is cybersecurity? | IBM
• Forming tomorrow’s cybersecurity landscape | Microsoft

The Cloud

The “cloud” is here and you simply MUST know about how this technology works and what it can do for you.

Amazon states that “Cloud computing is the on-demand delivery of compute power, database storage, applications, and other IT resources through a cloud services platform via the internet with pay-as-you-go pricing.”

Microsoft adds that “Businesses can take advantage of scalability and flexibility by not being limited to physical constraints of on-premises servers, the reliability of multiple data centers with multiple redundancies, customization by configuring servers to your preferences, and responsive load balancing that can easily respond to changing demands.”

• Microsoft Azure

• Amazon Web Services

Understanding Data

To be competitive, it is my belief that all business students should understand and be able to use the following technologies:

• Data Exploration and Analytics Software

  You should be able to analyze data using tools such as Tableau and Microsoft Power BI.

• Machine Learning

  David Chappell writes that "With lots of data about something, you can examine that data in intelligent ways to find patterns. And those patterns, which are typically too complex for you to detect yourself, can tell you how to solve a problem." Leading offerings include Azure Machine Learning from Microsoft and Amazon's Machine Learning on AWS.