A socio-technical plan

 



Emotion AI is a promising technology that is capable of analyzing slight cues in facial expressions, writings, and voices of people and respond accordingly – similar to the way a human being would. In the past decade, great strides have been taken to enhance the applications for emotion AI, these include important fields such as healthcare and psychology. There are numerous articles detailing how emotion AI can be highly beneficial for therapists, doctors, and their patients. I reckon that in the near-future, this technology will be widely accepted and utilized in the healthcare industry. However, the first step to its prosperous future relies on how well individuals can adapt to a voice-activated wearable gadget that can analyze their emotions and decipher whether they are blissful, sad or vexing based on the tone of their voices – this device called Dylan is currently being developed by Amazon (Day, 2019). Although several companies which include the likes of IBM Corp., Google, and Microsoft are building technologies that are designed to derive emotional states via audio, images, and various inputs – Amazon so far has taken the lead with Dylan. The Alexa voice software team in conjunction with Lab126, the hardware development group that built Amazon’s Fire phone, are the ones developing Dylan (Bernal, 2019). This gadget that will most likely be worn on the wrist will have microphones that will pair with software to sense an individual’s state of mind via their voice. 

 

Scope

Robots are becoming very skillful in detecting emotions via the faces of individuals – this is due to the consistent advancement of artificial intelligence and computer vision. However, due to the success of Amazon’s Echo speakers, they have made voice detection the core of their ambitions – hence the development of Dylan. This device could aid users in creating a consciousness of their emotional states, and also help in regulating their emotions better under challenging or stressful circumstances (Potamianos, & Narayanan, 2020). 

Furthermore, Dylan could be beneficial to therapist by predicting how patients will approach therapy and take necessary steps to make sure that the patients are thriving and continue in treatment. Nonetheless, like most AI models that rely on sensitive data to make informed decisions and forecasts, privacy is a valid concern – optimistically, this will be addresses accordingly in the near-future

                        

Purpose

Dylan is considered a health and wellness device with the purpose of positively enhancing the state of mind of its users. From providing resources on how to cope when nervousness is detected to helping users on how to express empathy, Dylan will be a game-changer in the field of Emotion AI.

 

  

Supporting Forces

Financial and technological forces support that adoption of Dylan. Amazon, having a market value of $1.14 trillion (Klebnikov, 2020) – has limitless resources at their disposal to make a voice-activated wearable gadget come to life. Moreover, with over one hundred-million Alexa devices that has been sold since its inception, there is a firm possibility of Dylan thriving in the global market (Bernal, 2019). Furthermore, the rapid advancement in AI research has paved the way for the likes of Dylan to prosper. Below is a graph illustrating the future sales of Apple smart watch and Dylan which is voice-activated and consists of several notifications like heart rate and irregular rhythms.

 


 

From the launch of Dylan in 2021, global sales will be 42 million units while Apple watch will be 32 million units – Dylan’s numbers will keep growing globally as more people see the health benefits of the device.

 

 

Challenging Forces

Legal forces may hamper the adoption of Dylan in the healthcare industry – HIPPA is a good example of such force. Although last year, Amazon unveiled a HIPPA complaint software that makes it possible for users to employ a voice assistant to receive and transmit secured health data (Farr, 2019) – laws tend to change, and they differ in various countries. 

 

Methodology

The most conducive method for Dylan is the Structured Design Process (SDP) due to its benefit of providing an elaborate understanding of how an issue is to be rectified. The waterfall model will be utilized in the software development process – the progress will flow through the phases of Initiation, Analysis, Design, Construction, Testing, Production, and Maintenance (Schwalbe, 2008).

 


 

Analytical Plan

In the U.S alone, over forty-nine million individuals experience a form of mental illness annually – approximately sixteen million adults are expected to experience depressive episodes, at least once (mami.org). With numbers like these, a revolutionary new device is necessary to aid in combating mental illness, hence the introduction of Dylan which will aid doctors to work more efficiently with patients via assisting with diagnosis and intervention. Furthermore, by it being a virtual therapist, it will aid in predicting and limiting the rate of suicide which is one of the leading causes of death in the U.S, claiming almost fifty-thousand lives in 2017 (cdc.gov). Dylan would be considered a success by directly or indirectly helping three-quarters of the users suffering from mental health issues. Data from surveys will be used to gauge the success of Dylan, it will be gathered from users, doctors, and therapists.

 

Anticipated Results

I expect Dylan to revolutionize the healthcare industry, particularly therapy within the next decade. As more data is gathered from users and therapists, Dylan will evolve in hardware and software.

 

Conclusion

Individuals with mental health issues outnumber the therapists that can assist. However, with the likes of Dylan – a voice-activated, wearable emotion AI device, the gap can reduce and save millions of lives globally. For instance, the pandemic we are all witnessing is taking a mental toll on everyone – some more than others, and not everyone has the luxury of affording a therapist. Nonetheless, Dylan will be of great benefit come post-Covid 19.

 

Areas of Future Research  

Emotion AI will consistently transform the healthcare industry because its potentials outweigh the risk – the juice is certainly worth the squeeze. Moreover, the continual enhancement of this technology by devoted specialists will pave the way for better AI models with the primary focus of helping individuals, reducing costs, improve quality of care, and broadening access. Last but not the least, privacy will need to be addressed wholeheartedly – without trust, a relationship between humans and computer systems will not endure the test of time.

 

 

 

 

 

 

References

Bernal, N. (2019, May 23). Amazon creates voice-activated device that recognizes human emotions. Retrieved September 6, 2020, from https://www.telegraph.co.uk/technology/2019/05/23/amazon-creating-voice-activated-wearable-device-can-recognise/

Day, M. (2019, May 23). Amazon Is Working on a Device That Can Read Human Emotions. Retrieved September 6, 2020, from https://www.bloomberg.com/news/articles/2019-05-23/amazon-is-working-on-a-wearable-device-that-reads-human-emotions

Farr, C. (2019, April 04). 'Alexa, find me a doctor': Amazon Alexa adds new medical skills. Retrieved September 6, 2020, from https://www.cnbc.com/2019/04/03/amazon-alexa-hipaa-compliant-adds-medical-skills.html

Klebnikov, S. (2020, April 14). Jeff Bezos Gets $6.4 Billion Richer As Amazon Stock Hits A New Record High. Retrieved September 6, 2020, from https://www.forbes.com/sites/sergeiklebnikov/2020/04/14/jeff-bezos-gets-63-billion-richer-as-amazon-stock-hits-a-new-record-high/#c141d2453b0a

Mental Health by the Numbers. (n.d.). Retrieved September 20, 2020, from https://www.nami.org/mhstats

Potamianos, A., & Narayanan, S. (2020, April 7). Why Emotion AI Is the Key to Mental Health Treatment. Retrieved September 6, 2020, from https://tdwi.org/articles/2020/04/07/adv-all-why-emotion-ai-key-to-mental-health-treatment.aspx

Schwalbe, K. (2008). Information Technology Project Management, Reprint. Cengage learning.

WISQARS Leading Causes of Death Reports. (n.d.). Retrieved September 20, 2020, from https://webappa.cdc.gov/sasweb/ncipc/leadcause.html

 

 

 

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