Smoke that codes: Women in tech, AI, & evolution of power | Krystal Trashawn Morris | TEDxChinotimba

Key Concepts

• Algorithmic Bias: The tendency of AI systems to reflect the biases present in the data they are trained on, leading to unfair or discriminatory outcomes.
• STEM Education: Education in Science, Technology, Engineering, and Mathematics, crucial for developing future innovators.
• Robotics as Thinking: The idea that robotics isn’t just about building machines, but about developing cognitive skills like problem-solving and strategic thinking.
• Representation in AI: The importance of diverse perspectives in the development of AI to ensure inclusivity and accuracy.
• Tech Ecosystem: A supportive environment providing equal access to technology and resources for all communities.
• Normalization of AI/Robotics: Integrating AI and robotics into core curriculum rather than treating them as electives.

The Hidden History & Future of Women in Technology & AI

The speaker emphasizes a critical issue in the development of Artificial Intelligence (AI): the underrepresentation of women and diverse perspectives, leading to potential biases and inaccuracies in the technology. She argues that AI isn’t simply teaching machines to think, but rather machines learning from us – including our biases. This learning process is incomplete without the full spectrum of human experience.

Historical Contributions of Women in Tech

The presentation begins by highlighting the often-overlooked contributions of women to the foundations of computing and technology. Specific examples are provided:

• Ada Lovelace (1800s): Credited with writing the world’s first algorithm, predating the existence of computers.
• Katherine Johnson: A mathematician who calculated trajectories for NASA space missions, essential for the success of the US space program.
• Grace Hopper: Inventor of the first compiler, a crucial tool that allowed computers to understand human language. Hopper’s work directly led to technologies like the conversational AI seen in platforms like Facebook, where the system anticipates user needs based on previous conversations. She posed the fundamental question: “Why can’t computers understand the human language?”

Robotics: Beyond the Machine

The speaker reframes the understanding of robotics, asserting that it’s not merely about the physical robot itself, but about the cognitive skills it fosters. Robotics cultivates:

• Cause and Effect: Understanding the relationship between actions and outcomes.
• Sequencing: The ability to order steps logically.
• Visualization & Conceptualization: Forming mental images and abstract ideas.
• Problem Decomposition: Breaking down complex problems into manageable steps.

These skills are transferable to various fields, including project management, data analysis, and everyday problem-solving. The process of building and refining a robot – imagining, strategizing, building, and iterating – is presented as a microcosm of the innovation process itself. The speaker states, “Robotics allows your mind an opportunity to imagine something, something that you've never seen before.”

The Danger of Biased AI & The Need for Diversity

A central argument is that AI systems will inherit and amplify existing societal biases if the teams developing them lack diversity. The speaker warns that if African-Americans, women, and educators are not involved in the development process, crucial elements like ethics, accuracy, and diversity will be absent. This leads to systems that don’t fully understand or cater to the needs of all users.

She illustrates this with a relatable example: an AI system asking, “Are you going to eat oatmeal or raisins?” without recognizing or understanding the existence of “grits,” a staple food in some cultures. This highlights how a lack of representation can result in systems that are culturally insensitive and incomplete. The speaker emphasizes that “diversity and representation should be a quality control measure, not an initiative.”

A Five-Step Framework for Inclusive Tech Education

The speaker proposes a five-step framework to address the lack of diversity and promote inclusive tech education:

1. Normalize AI and Robotics Early: Move AI and robotics from elective status to core curriculum, recognizing their importance in developing critical thinking skills.
2. Educate the Teachers: Provide teachers with the training and resources necessary to effectively teach AI and robotics.
3. Build a Tech Ecosystem: Ensure equitable access to technology and resources for all communities, regardless of income or location. Technology is presented as a need, not a luxury.
4. Show the Student What Tech Looks Like in Everyday Life: Connect technology to real-world applications in fields like transportation, irrigation, logistics, and medicine, bridging the gap between abstract concepts and practical relevance.
5. Diversity and Representation as Quality Control: Integrate diverse perspectives throughout the entire development process, viewing representation as essential for accuracy and inclusivity.

The "You're Not Done, You're Becoming" Philosophy

The speaker concludes with a personal philosophy encapsulated in her podcast title, “You’re Not Done, You’re Becoming.” This emphasizes the continuous process of growth and evolution, both individually and collectively. She encourages embracing change and opening one’s mind to the possibilities of AI and technology, believing that this is the path to building a brighter future. She states, “opening your mind up to the imagination and the realization of artificial intelligence, technology, robotics is how we build a brighter future.”

Synthesis

The presentation is a powerful call to action for greater inclusivity in the field of AI and technology. It underscores the historical contributions of women, redefines robotics as a tool for cognitive development, and warns against the dangers of biased AI. The proposed five-step framework provides a practical roadmap for fostering a more equitable and representative tech ecosystem, ultimately leading to AI systems that are more accurate, ethical, and beneficial for all of humanity. The core message is that a truly intelligent future requires the full participation and representation of all voices.