4 Surprising Ways Emotional AI is Making Life Better

It’s been a long night and you have driven for over 12 hours. The exhaustion is such that you are starting to blackout. As your eyes close and your head drops, the car slows down, moves to the shoulder, and stops. You wake up and realize your car saved your life. This is just one of many examples of how emotional AI can do good.

It doesn’t take much to see the ethical challenges of computer emotion recognition. Worse case scenarios of control and abuse quickly pop into mind. In this blog, I will explore the potential of emotional AI for human flourishing through 4 examples. We need to examine these technologies with a holistic view that weighs their benefits against their risks. Hence, here are 4 examples of how affecting computing could make life better.

1. Alert distracted drivers

Detecting signs of fatigue or alcohol intoxication early enough can be the difference between life and death. This applies not only to the driver but also to passengers and occupants of nearby vehicles. Emotional AI can detect blurry eyes, excessive blinking, and other facial signs that the driver is losing focus. As this mental state is detected early, the system can intervene through many means.

For example, it could alert the driver that they are too tired to drive. It could lower the windows or turn on loud music to jolt the driver into focus. More extreme interventions would include shocking the drivers’ hands through the steering wheel, and also slowing or stopping the car in a safe area.

As an additional benefit, this technology could also detect other volatile mental states such as anger, mania, and euphoria. This could lead to interventions like changing temperature, music, or even locking the car to keep the driver inside. In effect, this would not only reduce car accidents but could also diminish episodes of road rage.

2. Identify Depression in Patients

As those who suffer from depression would attest, the symptoms are not always clear to patients themselves. In fact, some of us can go years suffering the debilitating impacts of mental illness and think it is just part of life. This is especially true for those who live alone and therefore do not have the feedback of another close person to rely on.

Emotional AI trained to detect signs of depression in the face could therefore play an important role in moving clueless patients into awareness. While protecting privacy, in this case, is paramount, adding this to smartphones or AI companions could greatly help improve mental health.

Our faces let out a lot more than we realize. In this case, they may be alerting those around us that we are suffering in silence.

3. Detect emotional stress in workplaces

Workplaces can be toxic environments. In such cases, the fear of retaliation may keep workers from being honest with their peers or supervisors. A narrow focus on production and performance can easily make employees feel like machines. Emotional AI systems embedded through cameras and computer screens could detect a generalized increase in stress by collecting facial data from multiple employees. This in turn could be sent over to responsible leaders or regulators for appropriate intervention.

Is this too invasive? Well, it depends on how it is implemented. Many tracking systems are already present in workplaces where employee activity in computers and phones are monitored 24-7. Certainly, this could only work in places where there is trust, transparency and consent. It also depends on who has access to this data. An employee may not be comfortable with their bosses having this data but may agree to ceding this data to an independent group of peers.

4. Help autistic children socialize in schools

The last example shows how emotional AI can play a role in education. Autistic children process and respond to social queues differently. In this case, emotional AI in devices or a robot could gently teach the child to both interpret and respond to interactions with less anxiety.

This is not an attempt to put therapists or special-needs workers out of a job. It is instead an important enhancement to their essential work. The systems can be there to augment, expand and inform their work with each individual child. It can also provide a consistency that humans also fail to provide. This is especially important for kids who tend to thrive in structured environments. As in the cases above, privacy and consent must be at the forefront.

These are just a few examples of the promise of emotional AI. As industries start discovering and perfecting emotional AI technology, more use cases will emerge.

How does reading these examples make you feel? Do they sound promising or threatening? What other examples can you think of?

4 Reasons Why We Should be Teaching AI to Kids

In a previous blog, I talked about a multi-disciplinary approach to STEM education. In this blog I want to explore how teaching AI to kids can accomplish those goals while also introducing youngsters to an emerging technology that will greatly impact their future. If you are parent, you may be asking: why should my child learn about AI? Recently, the importance of STEM education has been emphasized by many stakeholders. Yet, what about learning AI that makes it different from other STEM subjects?

First it is important to better define what learning AI means. Lately, the AI term has been used for any instance a computer acts like a human. This varies from automation of tasks all the way to humanoids like Sophia . Are we talking about educating children to build sentient machines? No, at least not at first. The underlying technology that enables AI is machine learning. Simply put, as hinted by its name, these are algorithms that allow computers to learn directly from data or interaction with an environment rather than through programming. This is not a completely automated process as the data scientist and/or developer must still manage the processes of learning. Yet, at its essence, it is a new paradigm for how to use computers. We go from a programming in which we instruct computer to carry out tasks to machine learning where we feed the computer with data so it can discover patterns and learn tasks on its own. The question then is why should we teach AI (machine learning) to kids?

Exposes Them to Coding

Teaching AI to kids start with coding. While we’ll soon have advanced interfaces for machine learning, some that will allow a “drag-and-drop” experience, for now doing machine learning requires coding. That is good news for educational purposes. I don’t need to re-hash here the benefits of coding education. In recent years, there has been a tremendous push to get children to start coding early. Learning to code introduces them to a type of thinking that will help them later in life even if they do not become programmers. It requires logic and mathematical reasoning that can be applied to many endeavors.

Furthermore, generation Z grew up with computers, tablets and smart phones. They are very comfortable with using them and incorporating them into their world. Yet, while large tech companies have excelled in ensuring no child is left without a device, we have done a poor job in helping them understand what is under the hood of all this technology they use. Learning to code is a way to do exactly that: lift up the hood so they can see how these things work. Doing so, empowers them to become creators with technology rather than mere consumers.

Works Well With Gaming

The reality is that AI really started with games. One the first experiment with AI was to make a computer learn to play a game of Checkers. Hence, the combination between AI and gaming is rather complementary. While there are now some courses that teach children to build games, teaching AI goes a step further. They actually get to teach the computer to play games. This is important because games are a common part of their world. Teaching AI with games helps them engage in the topic by bringing it to a territory that is familiar to their imagination.

I suspect that gaming will increasingly become part of education in the near future. What once was the scourge of educators is turning out to be an effective tool to engage children in the learning process. There are clear objectives, instant rewards and challenges to overcome. Teaching machine learning with games, rides this wave of this and enhances it by giving them an opportunity to fine tune learning algorithms with objectives that captivate their imagination.

Promotes Data Fluency

Data is the electricity of the 21st century. Helping children understand how to collect, examine and analyze data sets them up for success in the world of big data. We are moving towards a society where data-driven methods are increasingly shaping our future. Consider for example how data is transforming fields like education, criminal courts and healthcare. This trends shows not signs of slowing down in the near future.

This trend will not be limited to IT jobs. As the sensors become more advanced, data collection will start happening in multi-form ways. Soon fitness programs will be informed, shaped and measured by body sensors that can provide more precise information about our bodies’ metabolism. Sports like Baseball  and Football are already being transformed by the use of data. Thus, it is not far-fetched to assume that they will eventually be working in jobs or building business that live on data. They may not all become data scientist or analysts, but they will likely need to be familiar with data processes.

Opens up Discussions About Our Humanity

Because AI looms large in Science-Fiction, the topic opens the way for discussions on Literature, Ethics, Philosophy and Social Studies. The development of AI forces us to re-consider what it means to be human. Hence, I believe it provides a great platform to add Humanities to an otherwise robust STEM subject. AI education can and should include a strong component of reading and writing.

Doing so develops critical thinking and also helps them connect the “how” with the “why”. It is not enough to just learn how to build AI applications but foremost why we should do it. What does it mean to outsource reasoning and decision-making to machines? How much automation can happen without compromising human flourishing? You may think these are adult question but we underestimate our children’s ability to reflect deeply about the destiny of humanity. They, more than us, need to think about these issues for they will inherit this world.

If we can start with them early, maybe they can make better choices and clean up the mess we have made. Also, teaching AI to kids can be a lot easier than we think.

Shifting Towards Education: A New Direction for 2018

Happy new year, everybody!

After a hiatus for the holiday season, I am now back to blogging with a renewed focus. For those of you who follow this blog or know me personally, last year was an encouraging beginning as I posted here my musings on the intersection between Theology and Artificial Intelligence. Above all, I’ve been encouraged by the conversation some of the posts have started.

After some reflection over the hiatus, I decided to shift the focus of the blog. As you may know, there are not a lot of voices speaking on this field. So the opportunities for making a contribution are vast. Moreover, I don’t see the topic of AI becoming less important in the coming years. The question I asked myself was how could I best contribute considering my skills, passion and knowledge. Promoting discussion on the topic was a good start but I was not satisfied in just being a thoughtful observer. The best insights often come from those who are immersed in practicing the field they are discussing.

Even as I type there are hundreds of AI startups starting to shape the future we’ll live in. There is a growing group of academics, consultants and enthusiasts speculating about what that would look like. Moreover, there are thousands of Data Scientists currently shaping the future of existing organizations building AI applications that will transform these enterprises for years to come. Eventually, politicians will catch up and start discussing policy and laws to regulate how AI is used.

While all this is happening, I think about my children. Will they have the tools they need to navigate this AI future? Will they be ready not only to survive but also thrive in this uncertain future?

When I look at the educational system they are in, it is clearly not up to the task. While I appreciate the wonderful work teachers do daily all over the world, the problem is systemic. The Western educational system was built in the last century to raise industrial workers. The economy required workers to learn a fixed trade that would last them through their lifetime.  Moreover, the academic system is always preparing students for the next level of education. Regardless of whether they pursue a job or continue their studies, a high school degree prepares the student for college, which prepares them for Masters’ work which, except for professional degrees, prepare them for pursuing PhDs. Hence, students are conditioned to excel within the academic “bubble” and have little interaction with the real world of jobs, leadership and service. Aside from a few exceptions, students are expected to figure out on their own how to apply the knowledge they learn into real workplace scenarios. While the system forces students to study separate disciplines, life is lived in multi-disciplinary spaces.

Staying out of the politically-charged discussion of “how to save our schools”, I rather work on how to offer something that will build on what the schools already offer. In my view, STEM (Science, Technology, Engineering and Math) education continues to be a challenge even as we have made progress in the past years. The concern I have with the current focus is that it separates these disciplines from humanities. In this way, students are taught only the “how” but rarely the “why” of STEM. This approach only perpetuates an uncritical consumerist relationship with technology, where we never stop to ask why are they being created in the first place and how they benefit humanity. Therefore the challenge is to engage young minds critically with STEM early on, empowering them to become creators with rather than consumers of technology.

While I can write about this frequently on the blog, being a detached analyst is not enough. That is why I am planning to develop actual learning experiences that address this gap. I am currently connecting with partners “glocally” to make that a reality. It will have both a classroom component as well as an online component. Stay tuned for more details.

How will that look like in aitheology.com?

The blog will flow from this journey of becoming an education entrepreneur. In this way, it serves as a platform for reflection, discussion, idea exchange and hopefully challenging some of you to join in this new endeavor. While I will continue to explore the themes of AI and theology, there will be an educational focus both in the topics discussed as well as in the way they are conveyed.

I also recognize that in our age, writing is not the most effective way to spread ideas and engage in conversation. Towards that end, I plan to add podcast in the near future so you can interact with AI theology in new ways. Finally, there will be plenty of opportunities for you to get involved in emerging projects.

I am excited for what this New Year will bring to us. I pray for wisdom and guidance in this new phase and I ask you to pray with me as well (if you are not religious, sending good thoughts would do).

How Do We Prepare the Next Generation For An AI Future?

In a previous blog, I described the trends that led to the current AI renaissance. In this blog, I want to talk about where AI is going and how we can prepare children and young adults to seize on the opportunities emerging from it. 

The Global Race For AI Innovation

AI startups are popping up everywhere, not only in the United States but in many places in the world. Canada just announced an investment of $93 Million for AI hubs in its largest cities. China may now be surpassing the US in government funding of AI initiatives as it leads deep learning (a subset AI technology) research along with its booming tech sector led by Baidu. Japan is also investing heavily on the area as a way to foster economic growth with an ageing population. Developing countries are also entering the race as African AI startups emerge and as Brazil hosts the first AI startup battle in Latin American soil. Everybody wants a piece of the AI revolution.

Even so, AI innovation is most likely to come from leading tech giants: Google, Amazon and Facebook. Google, through bold mergers and research investment, is aiming to become an AI-driven company. Amazon, who already leads the digital assistant market and the cloud business, is set to incorporate AI into all its core operations. Facebook is investing heavily in AI to better manage and customize content for 1.4 Billion users. These are just a few examples of how AI is shaping the future of the Tech industry. The company who can turn AI into viable commercial solutions will become the market leader of the future. The company that lags behind will most likely face obsolescence.

What Can We Do To Prepare?

How will this current race impact our future? AI will certainly eliminate jobs, but also create new opportunities. I want to focus on the latter part for now. Complete new industries will emerge as these technologies become widespread in business and government all over the world. Therefore, we need to prepare our kids and young adults so they can fill these new jobs. Hear me out, not every kid will grow up to become a data scientist, robotics engineer or software developer. Yet, as AI permeates different systems, there are some basic skills that the future worker and entrepreneur must be proficient at.

Math is a good example. Developing a strong foundation on math concepts will be crucial. That does not mean every kid must master Calculus by High School. However, we need to debunk the myth that math is only suitable for a minority of very intelligent people. There is no such thing, math is a language that all can learn. For that to happen, we must also change how we teach math. Common Core is an encouraging step in the right direction but much more needs to be done. Math needs to become more visual and more relevant to day-to-day problems.

Another skill is programming. Learning to code should become as important as learning to read. Not all kids turn into voracious readers as adults most know enough to be functional and informed citizens in their communities. Similarly, not all kids that learn coding will become developers but they should have sufficient knowledge to navigate the technological change that is ahead of us.

While technical skills are important, we cannot neglect critical thinking skills. Here is where I believe disciplines like theology and philosophy have a place. Because these technologies will become more and more interwoven with our humanity, we cannot afford to overemphasize the “how” at the cost of asking the “why” and the “what for”. In other words, we need to be constantly asking: “What does it mean to be human in an AI world?”. This will not come naturally in math and coding classes that focus only on skills.

The goal is not only to prepare future workers but empower them to become AI social entrepreneurs, ready to address problems untouched by big business or big government.

I propose an inter-disciplinary approach that teaches both technical skills along with critical thinking. Students should ask the questions of “why” and “what for” right when they learn the “how”.The goal is not only to prepare future workers but empower them to become AI social entrepreneurs, ready to address problems untouched by big business or big government. In the next blog, I’ll be discussing how a grassroots open-source AI movement could work parallel to the one already happening in the business and government sector.

That is when things get interesting.