/2024-group-03-cdsp

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MIT Emerging Talent - Group 3

Investigation of connections between depression development and excessive social media and AI chatbot usage

Overview

Mental health care is crucial for overall well-being, as it encompasses emotional, psychological, and social aspects of a person's life. One significant aspect of mental health in the digital age is the rise of internet addiction. With the increasing prevalence of smartphones, social media platforms, and development of AI tools, individuals are becoming more susceptible to excessive internet usage, leading to addiction. Our team decided to investigate how reliance on AI for emotional support or guidance may affect individuals' perceptions of their own mental well-being. Identifying potential risks allows for the development of safeguards and guidelines to minimize harm.

Problem statement

Please follow the link to read full problem statement

AI is the latest trend, we notice some people prefer chatting with AI instead of having conversation with friends, family members, or real people. The increasing preference for chatting with AI rather than real people presents a unique psychological landscape with potential implications for mental health. While conversing with AI can offer convenience, anonymity, and immediate responses, it also poses risks for certain individuals.

Research questions

Please follow the link to read full description for the research questions

  1. Are people who use Social media and AI chatbots a lot have a higher risk of depression development?
  2. Does people with diagnosed Clinical Depression have a higher risk of Digital addiction?
  3. Can AI chatbot provide the information which will be harmful for the person with the Depression?
  4. What is possible forecast for the Mental health with the increasing of popularity different AI tools?

Constraints

  1. Dataset availability (Lack of Data: There simply not be enough data available on the topic of interest to perform meaningful statistical analysis due to lack of studies or digital footprint in the area. Unreliable Data: Even if data is available, it may not be reliable. This could be due to biases in how the data was collected, errors in data entry, or inconsistencies in how data points are defined across different data sets)
  2. Data Privacy: As research involves human subjects and possibly sensitive personal data, adhering to privacy laws like GDPR and HIPAA is crucial. Getting consent, anonymizing data, and ensuring security can be challenging.
  3. Quality of Data: The data available might suffer from bias, inconsistencies, missing values, or it may not be granular enough for your specific research question

Methodology

Please follow the link to read full description for our approach to the system thinking and design thinking

  1. Empathize: From personal and close people experience we understand that Internet, social media and AI tools and give us not only benefits, but also some risks and their understanding helps us to decrease the harmful impact.
  2. Define the issue: We will explore the connections between growing of popularity of social media (10-5 years ago), AI chatbots (last two years) and level of depression in different countries.
  3. Ideas how to explore: While we don't have open data connected with AI usage, we want to analyze global trends for the level of depression since 2000 when Internet tarted to gain the popularity and no social media existed, then how it changed in 2010-2015 with growing of popularity of Social media, and then the most fresh data. We will explore the connections between development of social media and AI and diagnosed depression.
  4. Iterate: We are going to continuously refine our solution based on the feedback, insights, and new discoveries.

Data Collection and Analysis

Currently, open data on the influence of AI on mental health is unavailable. Therefore, we've chosen to investigate the influence of social media on mental health, assuming that these findings may highlight the potential effects of AI.

Data collection

Data analysis

Communicating results

Audience The target audience for our mental health awareness campaign is primarily aged between 20 and 40, possessing basic computer literacy and using social media and chatbots regularly. They are tech-savvy individuals with smartphones or computers and internet access, but they face constraints such as busy schedules, limited emotional vocabulary, and potential lack of support from their social circles. Financial limitations might have an impact on their ability to afford therapy, and they may not be fully aware of available mental health resources.

Artifact Our strategy involves utilizing social media marketing. These are the series of posts with the comparison between healthy ways of social media or AI tools usage and habits that may lead to harmful effects on mental health. Each post has graphics poster with a story about two persons, and a conclusion, or just a reference to some page with details We aim for our audience to realize the importance of real human connections, understand the limitations of chatbots, and feel empowered to seek professional help when needed. We hope they will use chatbots cautiously, be mindful of the risks of excessive use, and prioritize real-life relationships.

Full information

Results and overview document

We present our story and our message to our audience as an Instagram Account with a link to our Research Overview document

Presentation of our project

Final presentation