Self-Driving Cars

Whenever I think about the idea of driverless cars, I always imagine explorers that lived hundreds of years ago and who were attempting to create ink and paper maps of the new worlds that they had discovered. I think of this because of the unfathomable amount of mapped data that has had to be collected for even the idea of driverless cars to be realized, mapping not only entire cities but every single square inch of that city’s roads. What would Louis and Clark have said if we told them there were people who drove around cars that took pictures of everything and everywhere and created a real-life map of our world? They’d probably say: “what’s a car?”

This is all in the wake of Lyft making the announcement yesterday that they’ll be rolling out their first batch of driverless cars to begin testing on. Lyft has partnered with a company called nuTonomy, which could give them the biggest edge on their competitors if the first rollout is successful.

In another major partnership, Honda just announced yesterday that it has come together with a Chinese startup called SenseTime. This company is best known for its object recognition technology and artificial intelligence, and this merger is indicative of Honda’s intentions to provide self-driving cars by 2020. Their focus in buying this company is to gain knowledge on “risk prediction, action planning, and scene understanding” to better serve urban areas with safe cars.

I’m interested to see how well they are able to achieve this, in assessing risk when it comes to such a human endeavor like driving. Driving and vehicles isn’t exactly a social issue, and I think analyzing data for risks in driving will yield better results than attempts to translate speech and tone from huge databases into concrete and meaningful output and answers. With so many companies announcing their intentions to roll out their own version of the self-driving car, I’m curious to see how long it will be before I myself ride in one. Maggie Wilcoxon 

Final Team Blog Post

As our semester is coming to a close, that means the TechCats blog is also coming to an end. We hope you’ve enjoyed reading through all of our blogs on various of topics like: IT security, uses of big data, agile methodology,and then how to retain special employees. Hopefully through these few posts it kept our readers up to date on current technological trends in the world and also sparked interest in them to do research on their own. As we come to a close, let's take a look at a recap of what all of our bloggers had to say.

Parker: My blog posts all had to do with IT security. Over the last few months the media has been really interested in IT security especially pertaining to our election. This media spotlight has really caught my attention and has inspired me to want to go into the field of IT security after I graduate. The more involved IT gets in our daily lives, the greater importance it is to protect our personal information. No system is perfect, everybody knows that. People will always be trying to find loopholes to exploit and to get access to information they shouldn't, like with the Equifax Data Breach that I blogged about. The field of IT security is constantly growing, and I hope to be apart of it one day. A small sample of this growth can be found in my first blog when I talked about HackerOne. HackerOne was a group of hackers that were paid to find loopholes in systems, then report them to the company so they could be fixed. Just this group alone has created over $20.2 million in revenues, and they expect it to grow to $200 million by 2020. Hopefully you enjoyed my blogs, thanks for reading.

Samantha: I really enjoyed getting the opportunity to dig deeper into aspects of IT and how management differs in that field. My posts covered the general topic of IT management, from the Agile methodology perspective to ways managers can improve employee morale and satisfaction. Everyone can be the best for the job for a day, week, or even months but if management doesn’t invest back into their employee’s productivity will decline tremendously. I can’t wait to get started with my career and use the skills and experience I’ve gained to help create a better working environment with motivated employees.

Maggie: As I researched more about some of the aspects and opportunities of Big Data, the more divided I realized the tech world is on this subject. While some claim that the idea of data analytics is the be-all end-all answer to all of life’s questions, some disagree. While I read articles and book excerpts about using data to solve problems like how to map the human genome and predict how cancers spread, I also found writers who don’t believe there is a single project that can truly lock down the specific data-to-end result chain of transactions. While this side of the argument recognize the usefulness of data, there are those who are less than impressed with the current applications of it and the publicity that it garners in the tech industry. Learning more specifics about the potentials in Big Data, as well as some of the less-than-starstruck opinions on the subject has been an interesting journey and has opened me up to a lot more resources in regards to technology news and information.

Overall, we hope this blog sparked some interest in people outside of our class to stay current in today's technological world. Being up to date on the latest technological advancements is becoming more important everyday as it becomes more and more intertwined into our daily lives. This fast paced technological world is upon us, and it's our job to stay educated on the latest trends.

Parker Fifield

Sam Zobel

Maggie Wilcoxon

Big Data: Is It the Answer To Every Question?

I view the study of Big Data in a similar way that I see the study of economics, which tries to make mathematical and predictable sense of the human race. As Simon Chandler writes in an article for TechCrunch, “...[Big Data] will do little or nothing to alter the inherent subjectivity of the concepts used to divide this information into objects and relations.” Because computers don’t understand human concepts that can’t be reduced to ones and zeros, using databases and predictive analytics has failed in many projects attempting to answer questions about people and society. Economists are able to make exceptions in their models for the uncertainty of human behavior, but also attempts to use vast amounts of data to make predictions using formulas and numbers – using objective means to make subjective assertions.

The big focus on Big Data has been in marketing and advertising for businesses. Using data about past purchases, things that are purchased together, purchase timing, etc. etc. etc. Anything a business can collect information on. Although this has made huge changes in how products and coupons are advertised to consumers, the models that were created to produce those advertisements were created by humans or with major human input. Accurate models have to take into consideration the society and the culture of the person that they are targeting, and many other humanistic factors that can’t be directly translated into code.

When trying to predict when significant events (such as protests) were likely to happen, there were a number of huge database systems that came together to test their hypotheses. To test these systems, like the Lockheed Martin’s International Crisis Early Warning System (ICEWS) and Georgetown University’s Global Data on Events Language and Tone (GDELT), they measures how accurately they were able to predict protests in Latin America. They had mined news articles and social media to find trends, but found that the project ultimately failed with a little over 10% overlap. They largely attribute this to how “Automated systems can misclassify words.” Again bringing in the concept of subjectivity and trying to have a computer understand what is meant in tone, local dialects, and exaggeration.

While I think that Big Data is an incredibly exciting subject and will prove to be much more useful than the pessimists writing about it believe, I do agree that data alone will never be able to translate the human condition into binary. For Big Data to be useful and meaningful to areas that include any kind of human input, there has to be some kind of subjective influence. Until artificial intelligence is advanced enough to do away with human coders or developers, Big Data will be like typewriter keys with all of the paper and ink, and no author. Maggie Wilcoxon.

How to retain specialized employees

In a world with ever-changing technology, it is becoming extremely common for employees to specialize in their roles. It is nothing new for managers to have to supervise people who know more than they do about certain areas of technology, but it is a whole new world when money just isn’t enough to keep the best employees around.

Managers may appreciate their specialized employees; they may even thank and praise them from time to time, but is a nice pat on the back still enough? What steps are they taking to show their best employees that they value their expertise?

If you’re a manager or aspiring one and you don’t know the answer to these questions, here are a few ideas:

• ·        Make sure money is the root of any dissatisfaction – If you have truly maxed out the amount you are willing or able to pay your employees, this may not be the step for you. However, it seems careless not to ensure one of your prized employee, who’s earned better pay is getting it. This is no the be all end all solution to employee retention, when the employee has reached a satisfactory amount of money they will start to search for it in other areas.
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• ·       Value work-life balance – To assume being fully attentive at work is the most important aspect of your employee’s day is just plain naive. Due to emerging technologies the constrains of the traditional Monday through Friday 9 am – 5 pm work week have been eliminated. So, what is holding you back from giving your employees the flexibility to come in later or leave earlier in order to take the kids to school or indulge in their favorite hobbies?
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• ·         Make work fun – Not every day needs to be a circus act, but what’s the harm in having a little fun at the office? Plan monthly team outings, volunteer together, have a themed potluck. If your employees can have fun together they can be productive together. Removing some of the stuffy, formal work relationships will only boost office morale.
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• ·         Invest in career development and give them the opportunity to use it – You hire the best employees who will help you reach your business goals. They are staying with your company and organization when they likely have other options if they looked. Instead of using their knowledge and skills, invest in them as professionals. It will likely be one of the best returns you ever get on an investment.

I haven’t researched any science behind the ideas listed above, but I have experienced them personally. When your employees love coming into work each day, you’re doing something right. If you start to notice someone distancing themselves or having a couple rough weeks, it may be time to try something new. 

Samantha Zobel