Balloon Tree : Designing a framework to leverage casual thinking

Jul 31

Jul 31 Balloon Tree : Designing a framework to leverage casual thinking

PREMIS

With the exponential advancement of information technology and artificial intelligence, human intelligence is nowadays subjected to a whole new level of data input and output. Russell L. Ackoff argues that data and wisdom are connected through a hierarchy of comprehension. But then how can we leverage data in its different forms, including casual thought, to move up the “thinking” hierarchy?

riig final pitch_01_Rabih Ibrahim_EXP_05_02.jpg — CHALLENGE

The challenge we are faced with is succeeding in designing a sorting mechanism that helps human intelligence guide artificial intelligence in arranging, cataloging, and grouping information for faster comprehension and efficient output. It is also equally important to discover how artificial intelligence can have a deeper insight into human intelligence.

riig final pitch_01_Rabih Ibrahim_EXP_03_02 copy_02.jpg — SOLUTION

I developed an adaptive visual framework that enhances and accelerates pattern recognition by mapping human thought with online data and artificial intelligence on multiple hierarchies and matrices. Organic resource shows more complete body of understanding and new connections – ultimately elevating individual and collective capability in information acquisition and analysis.

INSIGHT

Beyond the complexities of artificial intelligence, data mining, and pattern infusion and recognition; the heart of the research and the key insight revolve around understanding the factor of time when it comes to data and thinking. They also tackle how time plays a role and how we can measure the “understanding” to the determinant of time.

riig final pitch_01_Rabih Ibrahim_EXP_12-1.jpg

RESEARCH + DELIVERABLES

Designing the balloon Tree as a solution took extensive research to tap into human intelligence. The mechanism in question, i.e information sorting and hierarchy ranking, is partially beyond the user’s power to control. The relationship between research and solution is not a direct one in this instance and thus some creative research methods were needed in addition to the basic ones.

INTERVIEW GAMES

One of the methods chosen for research is search games. Through sorting and pattern recognition, we came to understand human logic, and the relationship between intent and query. Three games were designed, targeting the way the contestants question, strategize, and synthesize in their quest to solve a game query.

OPEN-ENDED SURVEYS

Determining where artificial intelligence can play a role in supporting human intelligence is a challenge of its own we had to surmount. To ensure an array of participants and a variety of inputs, several open-ended surveys were drafted around the question: “where do you think you need artificial intelligence to support your own intelligence and why?”. The results were cross-checked through other search methods as well.

BUILD YOUR SEARCH ENGINE

At the convergence of this process, a tool was needed to reassess the research’s consolidated insights. Four imaginary search engines were created as sacrificial concepts. The features ranged between extremely functional and far-out creative to test their needs and widen the imagination of what-could-be. The participants were able to build their own information retrieval system, by mixing and matching features.

DESIGNED FRAMEWORK

Balloon Tree consists of a framework with a double growth system. It can grow from the solid information of the user (process named soil). It also can grow based on time spent online searching specific interests (process named Air). Together next to the other features, Balloon Tree aspires to create a neural network built around the user’s interests. In addition to above, it boasts clear archiving of the process to create a body of work the user can view, synthesize, build of, and customize.