HUMAN SEARCH ENGINE

Design Brief
Design a people based system for finding things out

Designers
Ruth Butler, Saranya Satheesh, Heng Qiu, Swaranjali Thankur, Xiaolin Kuang, Riya Jain, Rania, Ananya Manish.

Research Methodologies
Collaborative-participatory research

Key words
Search experience, human Interaction, social connectivity

The Human Search Engine

In the quest to redefine the search experience, our team commenced to design a Human Search Engine. For us this concept was not just about retrieving information but creating a system that embodied the essence of human interaction, intuition, and social connectivity. This blog critically analyzes our design process, highlighting our learnings, challenges, and the evolution of our project.

Understanding the Search Engine

Our initial step involved dissecting the computational search engine to understand its core functionalities: crawling, indexing, categorizing, and ranking data. In more human terms these elements could translate into:

Gathering/Storing data
Processing data
Sharing data.

With this foundational understanding our goal was not to replicate the digital search process but to explore the depths of a human based search engine that is of the people, by the people and for the people.

Research: The Pre-digital Era

As a group of millennials and Gen-Z’s we were clueless about how people navigated the search for knowledge before the digital era’s dominance. Employing stratified random sampling, we engaged with individuals on the streets who have experienced life before and during the digital search engine revolution.

Surprisingly, this exploration revealed a collective nostalgia for the tangible, social aspects of information search. While no one denied the convenience of ‘Google’, they missed the emotional and sensory engagements lost to modern digital solutions. To search something people created their own human search systems including calling families/friends, visiting museums or spending hours rummaging through library books. There was much more knowledge exchange and social skill development in the mere process of searching than there is today.

This insight shaped our vision for a search engine that is more focused towards how people find answers rather than the answer itself.

Experimentation Phase 1: Creating and Testing a human database

Our first step aimed to create a human database of information. We started with a simple experimentation wherein we used convenient sampling and asked our classmates to give us their remedies for cold and cough.

All the answers were written by the participants on a sticky note and then processed and ranked by one group member based on availability of ingredients, taste preferences and personal bias. The answers were then presented to the entire class.

This process revealed two critical insights:

We were mimicking a computational search engine and the elements involved in physically searching for an answer were missing.
We wanted the human search to be more participatory, human-centered and socially- oriented.

Experimentation Phase 2: Enhancing Participation

To foster engagement, we thought of letting our participants come up with new questions. Our next experimentation involved participants to leave a question on a board and answer an existing question on the board. The experimentation was done in three phases.

A) First, we tested this inside the campus and pinned our board to a wall of a common corridor. We got limited responses and realized that we need to motivate people to interact with our search engine.

B) To further add social engagement, we stood out on the streets of Elephant and Castle holding our prototype and encouraged passersby to interact. This yielded in social interactions, collective knowledge sharing and created a rich database.

C) Lastly instead of a pin board we tried using a human pinboard to make it weirder and more human. Although, the idea did not work as well as we thought as tactile interaction with a human body has its own set of complexities that we hadn’t investigated.

The questions and answers we collected as part of the database were relatable, funny and human. The human search engine was gathering and storing data well. The participants were also processing and accepting the data or answers.

However, the input (Question by Person A) and the output (Answer by person B) were emerging in different time frames. We were still missing the real sense of wonder and the gratification of searching and finding an answer.

Experimentation Phase 3: Embracing the Abstract

Since our fascination lay not just in the answers themselves but in the very act of searching since the very beginning, we wanted to simply focus on that. We decided to go completely abstract in our approach and let go of building a database and answering specific questions.

In a playful twist, one of our team members dressed up as a question while the other 4 members dressed up as answers. The experience was akin to hide and seek wherein we asked participants to find the lost answer in a given space.

A) For the first round we used convenient sampling and tried the experimentation in the LCC building. We soon realized that due of its abstract nature, participants weren’t entirely sure why one answer was right while the other was wrong. They were losing interest soon after interacting with the second answer and did not have the motivation to complete the experience.

B) Based on the response we altered our system. We streamlined the experience to feature just one correct answer and tried testing the validity of our system in a larger, busier space. Swapping out the missing banner for flyers, we dispersed these across Waterloo Station, hoping to spark curiosity and participation.

Alas, after over an hour and 30 flyers very few people were motivated enough to find the answer and people who tried to search gave up mid-process. This made us realise three things:

Even though our experience focused on the act of searching we were still missing the satisfaction of search and discovery and a purpose to the search.
The participatory and socially engaging aspects of our search engine felt contrived rather than organic.
What we all loved the most about this experimentation was the engaging missing poster of the lost answer. It reminded us of the missing posters on the streets.

Experimentation Phase 4: Riddles and real world engagement

Thinking we reached a dead end we decided to do a fun brainstorming activity and created a bunch of missing posters in under 5 mins. In most of our posters we noticed that there were clues to find the missing answer (Form/location/color), like pieces of a puzzle or a riddle.

Here are some interesting things that happened during the experimentation:

Out of the 30 searches we initiated with the flyers we got 15 responses back to us (Yay!)
The utilisation of costumes, and rewards created a cohesive, enjoyable search experience.
People in a group were much more likely to engage in the search experience. It was a fun activity for them to do together.
This approach not only facilitated a sense of community and shared discovery but also underscored the human-centric nature of our search engine.
Their journey of searching was participatory, and we could clearly see a sense of gratification when they figured out the answer.

Reflection and Future potential

The development of our Human Search Engine was a journey marked by exploration, experimentation, and learning. Our journey from mimicking digital processes to fostering human interaction was guided by collaborative-participatory design. This approach catalyzed the creation of a system that was not just built for people but, more importantly, shaped by them.

The potential of our human search engine extends into the realm of research methodology. The flyers, a key interaction point, could serve as an innovative tool for gathering data on human search behaviors. As participants navigate the clues and work towards a solution, their strategies and problem-solving techniques could provide a wealth of observational data.

This project truly helped us to re-imagine technology’s role in our lives and use design to foster connections that transcend the digital world.

References

Scariot, C.A., Heemann, A. and Padovani, S. (2012). Understanding the collaborative-participatory design. Work, 41, pp.2701–2705. doi:https://doi.org/10.3233/wor-2012-0656-2701.

Drennan, B. and Boal, A. (1994). Games for Actors and Non-Actors. Theatre Journal, 46(2), p.299. doi:https://doi.org/10.2307/3208476.

Escobar, A. (2018). Designs for the pluriverse : radical interdependence, autonomy, and the making of worlds. Durham: Duke University Press.

Ligon, E. and Fong, M.W.K. (2011). Transforming Design Thinking into Collaborative Innovation: Meeting the Emerging Neds and Demands of a Complex World Through Design Thinking and Collaborative Innovation. Iridescent, 1(1), pp.40–46. doi:https://doi.org/10.1080/19235003.2011.11782241.

The Blueprints