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I'm Reevaluating the Curve

Reevaluating the Curve

At the beginning of this fall semester, I began the exploration of emergent technologies; I initially positioned myself as an early majority adopter and now positioned myself as an early adopter. "People in the early adopter category seem to have the greatest degree of opinion leadership in most social systems. They provide advice and information sought by other adopters about an innovation" (Ou, n.d.). Originally, I was an early majority adopter; this categorization reflected my comfort level with adopting new technologies after they had been proven and widely accepted. I was drawn to the potential benefits of these technologies, particularly their ability to streamline processes, enhance productivity, and revolutionize industries.

However, as I dove deeper into the intricacies of AI, blockchain, and big data, my perspective began to evolve during my time in LDT 511. The initial excitement gave way to a more in-depth understanding of the ethical implications and lasting impact of these technologies. I started to question the rapid pace of technological advancement whether the advancement is a good thing or a bad thing and the potential consequences that might arise if we fail to consider the broader implications that could arise, especially when it comes to ethical concerns with technology.

One particular ethical dilemma that resonated with me was the potential for AI to perpetuate and amplify existing biases. As AI systems learn from vast amounts of data, they can inadvertently absorb and reinforce biases, leading to discriminatory outcomes. "The AI algorithm might produce biased outputs if the data is not diverse or representative" (Bias in AI, n.d.). This realization forced me to confront the darker side of technological advancement and to question the responsibility of developers and users in mitigating these risks and the concerns around data security.

For example, technologies found,

"Amazon’s one of the largest tech giants in the world. And so, it’s no surprise that they’re heavy users of machine learning and artificial intelligence. In 2015, Amazon realized that the algorithm used for hiring employees was found to be biased against women. The reason for that was because the algorithm was based on the number of resumes submitted over the past ten years, and since most of the applicants were men, it was trained to favor men over women" (Technologies, 2022).

This new awareness of the impact of AI and data security awareness has pushed me toward a more cautious approach to technology adoption. While I still believe in the potential for positive change, I now recognize the importance of critical thinking and ethical considerations. It is also important to consider who has access to data security when AI is used because, with so much data, the consequences of who has access to the data could be catastrophic. I am no longer content with simply accepting new technologies at face value. Instead, I am driven to understand the underlying mechanisms, the potential consequences, and the ethical implications.

This shift in perspective has not diminished my willingness to embrace new technologies, but it has refined how I approach new technology. I now want to be an informed and responsible adopter, one who is aware of the potential benefits and risks. I am committed to staying updated on the latest developments, engaging in critical discussions, and advocating for ethical guidelines and regulations. Thus, I have shifted from an early majority adopter to an early adopter. Mullany states, "If an early adopter can prove to themselves that your product is valuable, then they'll tell others in the early majority, who will put heavy weight on that opinion" (Mullany, 2021). In short, my perspective has become more refined and more research-based. 

Additionally, I believe it is crucial to foster a culture of digital literacy and critical thinking. By educating ourselves and others about the potential benefits and drawbacks of emerging technologies, we can empower individuals to make informed decisions and hold developers accountable. If we do not educate ourselves on the risks and benefits of AI, it makes it impossible to advocate for change.

To further delve into the ethical considerations of emerging technologies and their impact on society, let's explore some additional aspects, the good and the bad:

The Digital Divide and Accessibility

  • Unequal Access: Not everyone has equal access to technology, leading to a digital divide that can impact social and economic inequalities.
  • Accessibility: Ensuring that technology is accessible to people with disabilities is crucial to promoting inclusivity. We need to ensure that all learners feel supported no matter what kind of learner they are.

Privacy and Data Security

  • Data Privacy: The collection and use of personal data raise concerns about privacy and surveillance. The problem is especially with big data: The question is who has access to the data, and is the data secure? 
  • Data Security: Protecting sensitive data from cyberattacks is essential to safeguard individuals and organizations. We need to ensure that security is monitored constantly when it comes to large amounts of data. Blockchain is a great resource for data security; however, can organizations afford to have that technology, and can they afford someone to manage the technology?
For me, data and security are two of the many reasons my perspectives on emerging technology have changed so much. Before this semester, I failed to consider the ethical concerns around data and security. I knew data and security were important; however, I never thought about it being shared, especially when it comes to learner data that AI would need to have to help students. Without secure data management and security, such as blockchain, this creates so many concerns about ethics involving learner data, which is why it is something that is now a bigger priority to me compared to how I saw it at the beginning of the semester, because if it is not handled properly, then the student's personal information could be compromised. For example, imagine if a student was scoring poorly in a class because of a learning disability, and imagine if that data was shared with the entire school...

Job Displacement and Economic Disruption

  • Automation: As automation and AI advance, there is a risk of job displacement, leading to economic uncertainty that can impact the economy.

Environmental Impact

  • Sustainable Practices: Developing energy-efficient technologies and responsible disposal practices is crucial.

The Future of Work

  • Remote Work: The rise of remote work has reshaped traditional work arrangements, offering both benefits and challenges.
  • The Future of Jobs: As technology continues to evolve, new job roles and industries may emerge, requiring adaptability and lifelong learning, which can be a good thing.

The Role of Regulation and Policy

  • Ethical Guidelines: Developing and enforcing ethical guidelines for AI development and use can help mitigate potential harms.
  • Regulatory Frameworks: Governments and international organizations should work together to establish appropriate regulations to govern the use of emerging technologies.

By addressing these issues proactively, we can harness the potential of emerging technologies to create a more equitable, sustainable, and prosperous future. We must engage in ongoing dialogue and collaborate with policymakers to develop responsible guidelines and regulations.

As individuals, we can also play a role by being mindful of our own technology use, supporting ethical practices, and advocating for responsible innovation and use. By embracing these challenges and opportunities, we can shape a future where technology serves learners' best interests.

As I reflect on my journey through this semester, I am grateful for the opportunity to explore the complexities of emergent technologies. This experience has not only broadened my knowledge but also deepened my understanding of the ethical and social implications of technology advancements and the impact they can have on learning design and learners.

I am now more aware of my position on the innovation curve and the responsibility that comes with it. I am committed to using my knowledge and skills to promote responsible technology development and adoption. By embracing ethical considerations and fostering a culture of digital literacy and data security, we can harness the power of technology for good and mitigate the potential risks, thus creating a more unified system for learning design.

References:

Bias in AI. (n.d.). https://www.chapman.edu/ai/bias-in-ai.aspx#:~:text=It is important to recognize it is not diverse or representative.

Mullany, M. (2021, August 21). The Power of the Adoption Curve. https://www.linkedin.com/pulse/basics-adoption-curve-michael-mullany

Ou. (n.d.). index. https://www.ou.edu/deptcomm/dodjcc/groups/99A2/theories.htm

Technologies, D. (2022, September 20). Real-life Examples of Discriminating Artificial Intelligence  - Datatron. Datatron. https://datatron.com/real-life-examples-of-discriminating-artificial-intelligence/

 

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