Courtney Minich

I personally found this episode to be exceptionally interesting and a very realistic representation of the future of technology. In this episode, Martha loses her husband Ash, and her friend signs her up with a software that allows Martha to “talk to” Ash. The machine takes all of the data on Ash; text messages, email, videos, photos; and uses this data to mimic the voice and personality of Ash so Martha can feel like she is truly talking to him. To go a step further, the software allows for an upgraded feature: a replica of Ash, in bodily form. The robot is extremely realistic and can use Martha’s feedback to become more and more like Ash. The more data it has, the more it can predict how to react to situations. The creepiest part was when Martha told the robot Ash that the real Ash would have fought and cried if Martha told him to jump off the cliff. In response, the robot used this feedback and began to fight and cry.

Hello everyone,

I actually saw this episode about two months ago and felt it was one of the strangest but greatest episodes in the series. To me, it begins after Ash dies and Martha was signed up for the application. It started with messages that made Martha feel like she was conversing with Ash. It progressed to phone calls and social media. Martha began feeling like she was actually talking to Ash and started continuing her relationship with him (AI). The artificial intelligence became more of a reality to Martha when the “human” version of the AI came around. There was constant learning throughout the episode between trying to talk and sound like Ash, which progressed to physical appearance of the AI human body.

This episode of Black Mirror was very interesting and heart-wrenching. Martha lost her husband Ash and was so distraught that she accepted her friends advice to reconnect with Ash through AI. First, her friend explains that you can message with this machine and it will feel like you are really messaging Ash. The machine goes through ashes emails and social media to learn and mimic the way he talks and reacts. While messaging with the machine, it made her miss Ash even more so she decided to allow the machine to learn ashes voice and the way he talks so she could feel like she was actually talking to him again. After a while, just hearing his voice was not enough so she purchased a walking, talking AI Ash. From here, the machine continues to learn to be more like the real Ash. Martha tells the machine that Ash would have reacted a certain way, the machine learns, and mimics the behavior that Martha requests.

I found this episode very interesting and really made me think what future artificial intelligence may be in store for us. According to Wikipedia, machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to “learn” with data, without being explicitly programmed. Machine learning was presented when Martha’s friend or relative tried to help by adding her to a connection via email with her deceased husband Ash. The computer downloaded all data from Ash’s social media accounts and even his private accounts to mimic his voice and personality. Even as robot Ash he looked exactly the same, but Martha knew deep down inside it was not him. He didn’t respond in the same way her husband would, but when Martha made that clear he adjusted/learned to what she said he would say or do

Machine learning involves computers systems having the ability to learn using data that has not been explicitly programmed with the help of statistical techniques. Watching the requested episode of black mirror showed how advance artificial intelligence could possibly become in the near future. The episode portrayed various aspects of machine learning when artificial intelligence was able to mimic the personality of a dead person. AI was able to depict what the (dead) person could say or act, and talk like that person with the help of the data it was given from voice recordings, social media accounts, emails and anything related to that person. Machine learning was also present in the hand gestures used to tell what the computer to do, like throwing a file into the trash on the computer or uploading a file from one computer to another.

Watching this episode of Black Mirror I believe puts perspective on where AI can lead potentially. Machine learning is present throughout the episode in various stages. It was an interesting take on copping with a tragedy like losing a loved one especially after later realizing she was pregnant. It was interesting how Martha was able to send videos, audio and pictures in order to in order form a more personal AI. At the end of the day even though she went from talking and eventually the “robot” she come to conclusion that it was not the same. The hypothetical of AI was interesting to see where we can potentially go with it.

In that episode of “Black Mirror” we observed an excellent use of Artificial Intellegence and machine learning. From Ash’s facebook, tweeter or other social media sight’s posts, they collect all the metadata and through a softwer a replica f Ash’s was made with home Martha could talk initially but after sometimes she start living with him physically as a person. That replica could do almost everything what Ash used to do as a human being. But as far as feelings is concern, that replica didn’t have any feelings because it was a artiiiciial intelligent.

Machine learning involves the devising of complex models and algorithms which has the ability to predict certain outcomes. In the episode of “Be Right Back” in Season 2 of Black Mirror, this application could be seen throughout the episode with the software/robot that Martha bought to replace her dead husband Ash. By feeding the software with data obtained from Ash’s social media accounts from the past, such as feeds from Facebook and Twitter, and videos, the software is able to make predictions of how the deceased would probably act by using such information from the past. The learning is unsupervised and could be modified according to the user’s satisfaction level, i.e. it could improve its predictions to fit the user’s expectations, if the user thinks it is not imitating or predicting the original closely enough.

One major example of machine learning and AI is when Martha taught Ash to use terminology that was appropriate for the living form of Ash. Another instance is when Martha gives Ash instructions to breath while sleeping to appear more humanlike.

I believe that one of the biggest innovation over the last few years is the option to stream. This has affected various different company and products. As we discussed in class the beginning of stream (Netflix-one of the first) basically put companies that were in the movie and game rental industry out of business (Blockbuster,Hollywood Video,etc.). This has change mainly the cable company the most to this point. There are people “cutting the cord” and canceling cable packages to just go with a netflix or amazon in order to stream shows and movies. It seemed as though over the past few years the cable companies just kept raising their prices as if they would never become affected by this, but they were wrong. This simply has changed the original business model of how people watch tv an movies.

To me, I think the most important innovation in the last few years is PayPal and Venmo. I used these sites very much especially Venmo. Venmo allows me to send payments to my roommates for things like wifi and electric right from my mobile device. Additionally, these sites eliminate the need to find an ATM to withdraw cash. When someone sends money to someone else through Venmo the money appears instantly which then can be transferred into their bank account. These innovations has made sending money much simpler and convenient. Overall, PayPal and Venmo has eliminated the hassle of trying to find an ATM.

The most interesting innovation in the last few years would have to be streaming. The ability to stream music nowadays with consumers such as AppleMusic and Spotify has decreased CD sales. People are not buying physical CDs and stores like Best Buy will no longer carry CDs in stores starting in July. Music suppliers are not making sales and if more stores decide to move away from CD sales, then music suppliers will eventually go out of business. Some newer vehicles do not have CD players but the option to stream music via Bluetooth or connecting your phone to a port to steam. It’s quicker and easier to download music on to your device then taking a trip to the store.

Question – This week, we talked about disruptive innovation & how the rise of technology has completely changed many business and consumer driven actions. What do you think was the most interesting or important innovation in the last few years? Why? What has it done to the original business model?

Answer – One of the major topics we talked about in class was the use of money. To think, a couple decades ago, debit cards and credit cards were innovative “technology” that held your physical money digitally. Now, we have things such as wallet pay (apple pay, etc.). This is big when it comes to innovation because I don’t need cash and now I no longer need any of my debit/credit cards. I can use my phone, which has stored all of my cards in a virtual wallet. I can also check my credit limits and bank account funds on the apps from my phone, which makes having to go to an ATM machine or bank more obsolete.

Although distance learning has been an ongoing learning method for a couple of years, I believe technology has changed they way distance learning has been organized with the institution of online schools and universities. Popular online schools like the abcmouse.com, K12.com, and even Fox Online Business school, shows how technology is changing the ancient educational process. More adults are seen using this technology as a platform to go back to school, while more parents are also homeschooling their children. The online exam proctoring website Examity.com also serves as a major shift to the way exams are taken online. Although the traditional educational in-class learning is still dominant, I believe with the constant growth in technological innovations, the online learning might become the dominance in the future.

I believe the most important innovation technology has produced are businesses that can start and grow without inventory. For example, Uber and Lyft have been extremely successful, and they radically changed the way consumers catch rides. Both companies have no inventory of cars of their own; these businesses connect willing drivers to riders with the touch of a button, all done digitally and with the help of multiple algorithms. In addition, Air BnB is not a hotel with rooms of its own. It’s a company that connects willing hosts to consumers in need of housing. These businesses have utilized technology as leverage to not only creating their “inventory” but to scale their business rapidly. They truly have changed the way we do business because they have introduced a new model where inventory is created by the consumers and paid for their services.

The most important innovation of the last few years for me is advancement in online payment system. Such as Venmo, Apple Pay etc. These payment mathods brings biometric identification checking like finger print , Face ID or eye scan . These enhance the security of the transactions . Thus business become much more easier for the companies and also for the consumer.

As a Shopify owner, it’s important to have good data and an integrated system that enables users to have one clear view of the data and customer in order to keep the sales process running smoothly and prevent any issues. Since my Shopify business consists of dropshipping, having good data regarding the product stock and current prices from my suppliers is crucial to keeping customers happy. If the data is not automatically updated in one integrated system, I run the risk of using old data which can cause issues with customer orders, such as the product being out of stock or prices changing, leaving me with lower margins.

As a Finance major, ERPs can be very effective in streamline processes within the field of Finance. In a general sense, an ERP can provide an organization with an extensive view of how a company is doing in terms of income, expense, and profit. This total view of financials helps a company improve their financial control and manage risk. Good or bad data can have significant impact on my daily job because I’ll be using that data to make financial decisions. It’s very important that I analyze the data and determine the accuracy before using the data to supplement my decisions. All in all, well-developed ERPs and good data analytics gives Finance Professionals the ability to make better decisions.

As a marketing major, in my current career I work for an advertising company and part of my job is to create the information for the company to know who to advertise their services to. I use CRM databases on a daily basis to ensure that the clients that I bring into the company are listed in the correct order in which they sign on, their content is correct and corresponding to the proper drive. So, having the ability to funnel data quickly is crucial for me. If I had the wrong data sets matching with the wrong clients, I would probably lose my job. So I’m a big proponent of good data analytics.

As a business management major and in m current role as a Senior Specialist at CTCA, it is crucial to have an integrated system that allows us to collect good date in one view. I am on SalesForce daily. If I don’t document my conversations or any documents sent to me from a patient or stakeholder, then it may cause a delay in getting a patient to schedule an evaluation. Time is of the essence for these patients and we want to provide them with the information necessary to schedule an evaluation. I can’t do my job well unless I have all the information that’s normally entered in SalesForce such as their diagnosis, clinical history, insurance, demographic information and any barriers I need to know of to help overcome. SalesForce is our means of communication for the Oncology Information Specialist team so if there is no good data in the system, we all can’t perform at our best or provide the patient with information to help.

As a marketing major, and possible future pharmaceutical sales rep, ERT’s and Data Analytics are vital to be up to date and correct. They are a very important part in making things run smoothly. For example, if the data analytics were incorrect in saying that a doctor did NOT want a new drug/ improved drug that we tried to market he/she, and they never received it when in reality they were expecting a shipment in for several patients, this could cost you your job, and even risk someone’s health if things are incorrect and not running smoothly. This is why ERT’s and Data Analytics are important and shows how easily it could affect this job position if not handled correctly.

In my future career, as an MIS major, I believe that implementing and updating these types of systems will be crucial to my success. They are so important because they are the operation behind how businesses do business. If I have an understanding of how ERPs and Data Analytics work, I can potentially be part of a team that works on implementing these systems, or on a team that manages the data and uses that to leverage business decisions. Good data’s impact on my daily job will probably be much easier to work with; however, I believe that sifting through bad data to find patterns could also draw my interest and become a worthwhile project.

As a marketing major, ERPs and data analytics is crucial in order to target the right consumers. When performing research on the population in order to segment and target, we need as much accurate data as possible in order to make decisions and plan marketing initiatives for the targeted consumers. Good data will help accurately solve problems and create better decisions. Having faulty data creates a high risk of not being able to market to the correct consumers, which would ultimately cause failure in a marketing team.

As a Business Management major, having good data on a job site should be key to running a smooth and financially stable business. Good data reviewed and evaluated by major functions of a business like accounting, marketing, human resources and others help each one of them make good decisions that could benefit the others and also run the company. Bad data only brings chaos into the company. The company could be left in shambles if this bad data is shared and executed by the functions of the company.

In my current job, it is a big issue to have bad data. Since I work in insurance, it is important that we have good data on the participants that enroll in core and voluntary benefits. We need to ensure that the participant’s information such as date of birth, social security number, coverage elected is accurate so they get the correct coverage they applied for on time.

As a Finance Major, I think ERP could play very important role in Investment Banking sector. It’ll create a very effective relation within the several department of the banking company, which will give a clear idea of company’s income, expenses, amount of equity the company has or how much capital the company needs.
As I am thinking of persuading my career in Investment Banking, I think data analytics will give me a strong idea to make any big decision. If I have to make a decision to create a capital for other companies , Government or any other entities, I have to have data in my hand. Those data would be good data or bad data. By analyzing these data I have to make the most appropriate decision. So, I think Data analytics will play a significant role in my future career.

In my job, I work for a government agency. We currently have in my department a legacy system where two major systems work partially independent of each other while still containing virtually the same data for the same function. We are always having trouble reconciling a time sensitive situation because data from one system often takes time to update to the other.
This problem will cause time and sometimes monetary losses by the public because the information needed is often 24 hours away from being current. Though it is tough for a government agency to justify the great expenditure needed to update to ERP’s, I can see our agency becoming a much more useful entity for the public.

As a Supply Chain Management major, I think that ERPs and Data Analytics play a significant role in my future career, and in any position that I may come across applying. ERPs have originated from the desire to coordinate manufacturing procedures earlier, and definitely has its roots in the operations management field. In a increasingly more technological reliant world, more processes in the supply chain are being automated with the data that firms have acquired from customers, and could significantly cut costs and expedite the business transaction process. Having good data is a must for the operations to run smoothly and accurately, on the contrary, bad data will cause errors and bottleneck in the entire system and have devastating consequences for the company’s reputation.

As I work in supply chain field it is very important to collect good data. We use our system to communicate through the various stages of production to finished goods. If at any point there was bad data collected it could have a huge domino effect. Example would be the thickness of the medical wire something as small as a centimeter off the end product would not be correct and essentially have to be re done. With my experience in various systems you have to pay close attention to the data that you are entering no matter what stage or department. You want anyone that uses the system to be able to pick up where you left off and as for the customers you want them to be able to navigate with as minimal issues as possible.

As my major is Business, it is very important to collect good data on customers. One part of my job is specializing in solutions for our clients. In order to propose to them a good price, I have to collect good data on their costs and computer usages.