Don’t forget to complete the online course evaluation for this class!
You can access the ESFF site here. The deadline is May 2 (well, technically May 3 at 8:00 AM, but are you really going to get up early on May 3 to do it?).
It only will take you five minutes, but it is important.
Some things about the course evaluations:
- Your feedback is anonymous.
- I don’t get the results until after the semester is completely over.
- I really look at the feedback and use it to make changes for future semesters.
Here is the link to the recording.
Here is the link to the recording.
As artificial intelligence continues to grow more advanced, many questions now need to be considered regarding risk management and insurance. One huge question is who is at fault when an AI powered technology that makes its own decisions does something that harms others? The very straight forward example provided by Business Insurance was what happens when an AI powered car hits someone? But the question even stretches further than that because “AI will have an impact on such diverse areas such as the economy, the environment, politics and the legal system”. Obviously there are many ethical questions that come into play here too but it will be very interesting to see how these innovations are handled from an insurance perspective.
Who do you think should be held responsible for the decisions made by AI?
Salesforce, in September 2016, bet on AI to grow its customer relationship management and it looks like that bet has slowly, but surely, paid off. In the two years since it was introduced, Salesforce’s Einstein has delivered millions upon millions of predictions to Salesforce customers and the company is continuing to grow its power by acquiring more data accessing capabilities for Einstein to deepen its abilities.
This has also provided financial results as Salesforce has seen 25% growth in the previous Jan 31 fiscal year with stocks skyrocketing as a result. Now Salesforce must change the face of its AI, making sure that consumers see the deep skill difference between Salesforce’s Einstein and the simple language processing skills of assistants like Alexa and Siri.
Artificial Intelligence is becoming or is already a part of every industry that exists. It will only continue to expand further because it has proven benefits with businesses and consumers. Health care is one of the many industries that AI has impacted. According to Accenture Research, their data predicts from 2018 to 2022, employment in health care will increase by 15% and revenues by 49%. This will be due to the greater interaction between humans and machines. Specifically in health care, AI has brought unique capabilities to the industry. AI now has the capability to identify breast cancer cells with greater precision, increasing accuracy from 96% to 99.5%. Also, with elder care, robots are now reminding patients to take medication and lead them through physical and cognitive exercises. And lastly, there are AI technology that provide greater precision with surgeries. Surgeons are able to sit at a console and nudge the joystick which controls the robotic arms. This eliminates the possibility of human jitters and involuntary tremors. These are a few of the many ways machines are advancing in health care industries. At the pace where AI advancement is growing, will this continue to be proven beneficial or will it come to a point where it becomes extreme?
As the population of the elderly increases, the need for technology has been steadily progressing to assist those who need it. The basic categories that affect these people are healthcare and lifestyle. For healthcare, there are medical technologies that have been introduced to assist. These tools will most likely require the help of an elderly person’s children or caregiver, so there are some barriers to entry. Additionally, there will not be as many private care options, as explained by the “caregiving cliff”, but AI could offer a cheaper alternative to some of the technological issues that occur. For example, the 3506 project, Memory Lane is a product that is geared to those with memory loss, and specifically the elderly. Although these technologies may be difficult for the elderly to understand, it can bring families together and create stronger bonds and connections. A drawback of these applications is also the cost of the products. This can create a socioeconomic divide between those who can afford it and those who cannot. Do you think that the elderly will be able to overcome the AI learning curve? Will caregivers be replaced by AI in terms of technological advances? How do you think AI will advance in the future to aid the younger population?
Very few organizations provide consistently stellar customer service. Customers expect organizations to tend to their needs, and if the organization fails to do so, there is a chance that the customer will chose to instead spend money on a competing or substitute product. Some organizations have attempted to implement artificial intelligence in call centers as a way to reduce labor costs and streamline customer service processes. However, as many of us are far too familiar with, artificial intelligence in customer service hasn’t lived up to the hype. The first example that comes to my mind is Amtrak’s “Julie,” who fields all of Amtrak’s calls to get basic information before transferring customers over to an agent. There has not been a time where I haven’t had to read my six-character booking number to Julie at least five times before she finally understood all of the characters. I’m upset before the system even has the chance to transfer me to an agent. Amtrak’s Julie represents a traditionally reactive customer service model, where the customer reaches out to the company with an inquiry, and a support agent reacts to the inquiry. Salesforce & Cisco flipped the traditional customer service model upside-down, and recently partnered to help organizations use data to become more proactive when it comes to customer service. The two technology conglomerates bring together Salesforce’s Service Cloud and Cisco’s Contact Center to create a single agent desktop, where the agent is empowered to quickly handle every customer interaction with personalization and data-driven insights. All customer inquiries come through the Contact Center platform, where Service Cloud intelligence automatically classifies the case based on user history and trends. Contact Center then routes the call to the agent best equipped to tackle the case, along with recommended responses and rich details on the customer from all departments within the company. The more the agent uses the system, the smarter and more predictive it becomes, all benefiting the customer in the end of the day. By merging two major platforms in to a single desktop solution, Salesforce and Cisco bring new-market disruption to customer service. Has anybody experienced stellar customer service that somehow incorporated artificial intelligence? How else do you think artificial intelligence or tomorrow’s high tech could impact the future of customer service?
In the face of a technological dawning, consumers and business markets are facing new issues every day. As Artificial Intelligence becomes both available and usable for the everyday consumer, there are new issues and controversies arising daily. Two weekends ago, a self-driving uber vehicle struck a 49-year old pedestrian woman, causing Uber to temporarily shut down the self-driving testing programs.
While there is no denying the tragedy and hurt surrounding the event, in comparison to other business endeavors much harm has been done without completely halting operations. This could perhaps be sensationalist media using emotion to evoke stronger reactions out of its viewers than the story itself permits. Sensationalism has been used heavily as of lately and this is simply an example of how it can be utilized, especially in the case of a new and rather unknown technology.
From a technology advocate perspective, events like this are deeply disheartening both for the hurt technology caused, as well as for the blow to the development of the technology. Those who were excited about the advancement of this consumer AI technology must now accept that perhaps it isn’t ready for market. The events that have occurred prove that the technology still needs work, and therefore cannot be fully implemented as of yet. The growth of consumer-utilized AI is an exciting concept, but society isn’t ready and nor is the market. Until situations like this dwindle, these types of technology will not stand and thrive.
TV ratings have historically been the number one measure used in determining how successful a show is, and therefore the price to advertise during that show. However, in recent years, marketers are turning to new measures promising to provide information regarding user attention and even emotion. Companies like TVision are using cognitive computing to train facial recognition software to recognize attention and emotion of users watching. These companies will pay samples of people to simply keep a camera on while they watch TV, often the Microsoft Kinect Sensor. The software behind the sensor is constantly learning more and more how to identify emotions through facial expression. This leads to data on what shows viewers are more engaged with while watching, and even what show’s viewers are more engaged with commercials. After all, if you were an advertiser wouldn’t you rather pay to show your commercial to people you know are watching? Many people turn shows on and don’t pay attention, or they leave them on as they do other things around the house. These shows may have high viewership, but the viewers may not actually be paying attention. For example, one study done by TVision showed that Shark Tank ranked amongst the highest in their attention rating. This makes sense because viewers are highly engaged with new business ideas and the suspense of a potential offer. Also, as you can imagine, commercial attention scores during the Super Bowl were very high. The more the AI software learns the more accurate and reliable this data will become. This system could potential replace ratings as the primary source of determining the value of an advertisement slot.