top of page
  • Robert Murtha

Deep Collaboration is Key to Maintaining Ethical AI

Updated: Apr 7


A person hugging a robot. Line Drawing.

As social creatures, human interaction is a fundamental part of our existence. Our ability to connect with others and build relationships is critical to our mental health and overall well-being. Studies have demonstrated that regular social interaction can offer a variety of benefits for our mental health, such as decreasing the likelihood of depression and anxiety, enhancing our mood, and promoting feelings of self-worth and inclusion. Additionally, our opinions as social creatures could vary wildly. At this stage of AI Inoovation, our opinions are extremely powerful.


As creators, we're empowered to drastically impact how AI's developed due to the manual nature of current algorithm training processes. Collaboration can and will keep biases in check and lead to more humane, inclusive AI development that helps with maintaining Ethical AI outcomes.


Two people collaborating on an Ipad

How Does Design Thinking Encourage Collaboration and Help with Maintaining Ethical AI?


Silicon Valley has long been recognized as a hub of innovation and technology, and design thinking has played a significant role in driving collaboration for software development in this region. One example of this is the "design sprint" method, which was pioneered by Google Ventures and has since been adopted by many Silicon Valley tech companies.


A design sprint involves a multi-disciplinary team coming together for a focused period of time to work on a specific problem or challenge. The team is led by a facilitator who guides them through a series of exercises that encourage creative thinking and collaboration. These exercises include brainstorming, prototyping, and user testing.

By using design thinking and design sprint methods, Silicon Valley companies have been able to break down traditional barriers between teams and encourage more cross-functional collaboration. This approach has also helped to shift the focus from individual contributions to team contributions, where everyone's unique skills and perspectives are valued and leveraged.


In addition to design sprints, other design thinking methods such as empathy mapping and journey mapping have also been used to encourage collaboration for software development in Silicon Valley. These tools help teams to better understand the needs and perspectives of end-users, which in turn helps to create more user-centric products and services.


Magical and futuristic face of a woman

How Will Deep Collaboration Lead to Better Artificial Intelligence Results?


When we think of Artificial Intelligence, we think of accelerated automation, and a machine that can achieve the same outcomes as humans, with way fewer constraints. AI food is data and computation which is powered by energy. AI doesn't need sleep, shelter, or water. The possibilities of both enhancements and issues are endless. That's why Ethical AI, or the practice of developing artificial intelligence systems that align with ethical principles and values, has become an increasingly important topic in the field of technology.


As AI systems become more sophisticated and integrated into our daily lives, there is a growing recognition that they have the potential to affect not just technical or business concerns, but also ethical and social ones. The ethical considerations of AI are particularly important because these systems can have a significant impact on individuals and society as a whole. For example, AI algorithms used in hiring processes can perpetuate biases and discrimination, while AI used in surveillance can infringe on privacy rights. By prioritizing ethical considerations in the development and deployment of AI, we can help ensure that these systems are used in a way that benefits society and promotes the greater good, rather than causing harm or perpetuating existing inequalities.


What can change that? Human interaction and deep collaboration. Pairing human's together and creating meaningful policy that helps navigate creative feature development for AI, will greatly reduce risk in the development of AI holistically, as well as the training of models that contribute to automated outcomes. By bringing together diverse teams of experts, including engineers, data scientists, social scientists, ethicists, and end-users, we can leverage the strengths of both humans and machines to develop AI systems that are more accurate, reliable, and inclusive.


Collaborative approaches can help to identify potential biases in data or algorithms, incorporate feedback from end-users, and ensure that AI systems are developed in a way that aligns with ethical principles and values. In addition, human collaboration can help to identify new applications for AI that may not have been previously considered, leading to more innovative and impactful solutions. Ultimately, human collaboration is essential for creating better AI results that are more effective, ethical, and beneficial for society.


Two women smiling and embracing each other.


How Does Culture Impact Deep Automation and AI Development?


I always say: "Build with love, not with hate." Your state of mind impacts the features you prioritize, the way you annotate data, and the types of data that you use to train models. In addition to policies, create a strong culture of love that surrounds AI Development teams to create a "force-field" that passively encourages kindness, always. This force-field will continuously encourage teams to incorporate empathy into the features they develop. It will provide a wonderful baseline to encourage kind outcomes for both humans and machines.


How can you start encouraging this empathetic culture that's self-aware and that's focused on creating "Kind AI"? Develop ceremonies where teams collaborate and research. When you're developing AI, you're effectively coding behavioral trends and psychological decision trees into an application. Create a deep relationship with behavioral science, research product research collateral like Laws of UX. Prioritize deep collaboration continuously throughout your project.


At Adjective, we're behavioral science and AI nerds. We're excited to help develop new ethical AI and push the limits surrounding human-centered automation. It's our goal to give people back their time while simultaneously making their environments safer using ethical AI. If you're as passionate about human-centered automation as we are, reach out to us here!

Comentários


bottom of page