Digital Anthropology

What is Digital Anthropology and How to do it ?

January 25, 2021

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As per the definition of Anthropology – It is the scientific study of humans, human behavior, and their societies in the past and present study patterns of behavior of human society.

Digital Anthropology is the anthropological study of the relationship between humans and digital-era technology.

How anthropology has helped us in understanding the evolution of the human race

To understand the relevance of anthropology, think of human life before electricity was invented. Our ancestors had a very different lifestyle that time. They used to get up early and finish all the work before sunset.

Before the industrial revolution started, a major human population was involved in the work, where physical power was required ( For Example, agriculture, stone cutting, transportation of goods…). To improve the productivity here, we came up with various tools & machines.

To run these machines, we used various methods. Like, initially, we used steam power. So many plants were built near rivers.

Once electricity came, we started building plants, at faraway places. Our various other habits got changed post electricity. Many industries came up, which revolved around ‘nightlife’.

We could not have imagined a city like Las-Vegas in that era. After electricity came, many other changes happened in our personal and business life. So we can safely conclude that electricity had helped the human race to evolve to the next stage.

Now you can relate to various inventions like the telephone, cars, the airplane…, which had helped the human race to pivot & improve overall productivity, ability to work from faraway places….

Digital and & new habits

My firm belief is that Digital has the same power and this will also help the human race to evolve to the next level. Hence, it is vital for us to deeply understand digital anthropology, if we want to future proof our digital transformation journey.

Let me give some examples here.

Today, many of us have a smart cameras and we have got the habit of taking selfies & immediately posting the same on social media platforms. During 2020 COVID time, we were able to work from home. We were also able to remain at home & were able to watch movies, read books, order groceries.

Now many companies are talking of making ‘ Work from home’ a normal practice, even after COVID. Remember, nothing new got invented during this COVID time. Working from home & watching the movie at home was possible earlier also. But somewhere in our mind, there was a deep-rooted belief that ‘WFH’ for long period can’t happen.

Now that belief has got shattered ( or should I say that mother nature taught us many things during COVID times & taught us what all is possible).

In my opinion, we still have to harness the full power of digital. Again, one of the big reasons is, deep-rooted beliefs in our mind.

I guess same thought was prevalent when cars came. Everyone thought/worried about, what will happen to the horse-cart. In my opinion, only horses lost the job and human-adapted to new conditions/took up driver job etc

So on a similar note, now one topic up for discussion is ‘ what will happen when machines start doing all the work, which is getting done by humans’.

Yes, we have machines, which have a good ‘human-like’ mind. These machines can help us in doing various calculation works. So from initial calculators to the current robots, these machines had helped in doing various ‘calculation’ work faster & error-free.

Digital anthropology & work of future

We need not worry about future of current work. Rather we should start thinking about the work, which will be required in future. Instead of worrying about automation, we need to start thinking about ‘ augmentation with machines’.

As per various research, it is established that the human mind consists of two parts. Conscious Mind & Sub-Conscious Mind. Our conscious mind is good at calculation, remembering various things & doing logical work.

Our sub-conscious mind is good at various soft skills & emotional intelligence.

Remember, machines can have a good ‘human-like conscious mind’. But they will not have a subconscious mind.

Humans, who have good control over their sub-conscious minds, will be successful in future. That will help evolve the human race to the next level.

Let me give some examples here. Based on customer consent, various new era technology companies ( Facebook, Amazon, Google, Netflix…) are collecting data based on our behavior ( where we traveled, which type of movies we saw, which type of clothes we ordered). Later that data is used to influence our sub-conscious mind. That is, you start seeing recommendations for products, which matches your taste.

First you see what you like, later you start liking, whatever is shown to you.

Many of us, are worried because in our current education system, no one teaches the importance of soft-skills & emotional intelligence. We know, how computer works but don’t know, how our own mind works. In past, our various saints also used to meditate long hours, to understand & control their subconscious mind.

In coming days

Soft skills and EQ will be better rewarded than certification and IQ
Cognitive flexibility
Judgment and decision-making over routine data scanning abilities
Creativity and critical-thinking skills

So in nutshell, I will say that we should welcome the machines/robots/computers in our life. They will do various repetitive, monotonous work. The human mind will be free to do various creative work, spend good time with our family ( elders & children), take care/console persons who is depressed.

Each human being is different & by that definition, each human being has a different sub-conscious mind. Our current world population around 8 billion. So even 1/8 of this population ( that is 1 billion human beings), collectively harness the power of their subconscious mind ( creativity, compassion, empathy, curiosity, gratitude.), it will do wonders in taking human race to next level.

What is Digital Anthropology for Enterprise AI?

Digital Anthropology for Enterprise AI is the discipline of understanding how people, institutions, processes, behaviors, exceptions, relationships, and real-world contexts are represented inside digital systems before AI systems are allowed to reason, decide, or act.

It focuses on ensuring that Enterprise AI operates on meaningful representations of reality rather than isolated data records.

According to Raktim Singh, Digital Anthropology serves as the bridge between human reality and machine intelligence.

Why is Digital Anthropology important for Enterprise AI?

Digital Anthropology is important because AI systems do not operate directly on reality. They operate on representations of reality.

If an organization misunderstands customers, employees, assets, risks, operations, or business context, AI systems can amplify those misunderstandings at scale.

Digital Anthropology helps organizations understand the human, organizational, and institutional realities that exist behind enterprise data.

What is the relationship between Digital Anthropology and Enterprise AI?

Enterprise AI depends on understanding reality before automating decisions.

Digital Anthropology studies how organizations actually function, including informal processes, workarounds, tacit knowledge, decision patterns, and behavioral context.

This understanding helps organizations create better representations for AI systems to reason over.

How is Digital Anthropology different from Digital Transformation?

Digital Transformation focuses on digitizing processes, systems, workflows, and customer experiences.

Digital Anthropology focuses on understanding the reality behind those processes.

Digital Transformation asks:

How do we digitize the enterprise?

Digital Anthropology asks:

What reality are we representing inside the enterprise?

According to Raktim Singh, many digital transformation initiatives failed because they digitized activity without adequately representing meaning.

What is the relationship between Digital Anthropology and the Representation Economy?

Digital Anthropology helps organizations understand reality.

The Representation Economy explains why representing reality accurately creates economic value.

According to Raktim Singh’s Representation Economy framework, future competitive advantage will increasingly depend on how effectively institutions represent customers, assets, risks, operations, obligations, and ecosystems before making decisions.

What is the relationship between Digital Anthropology and SENSE–CORE–DRIVER?

Digital Anthropology identifies what reality must be represented.

The SENSE–CORE–DRIVER framework provides the architecture for operationalizing that representation.

In the framework:

SENSE makes reality machine-legible.

CORE reasons over represented reality.

DRIVER governs execution, accountability, identity, verification, and recourse.

Together, they help organizations build trustworthy Enterprise AI systems.

Does Enterprise AI fail because of poor AI models?

Not always.

Many Enterprise AI initiatives fail even when models perform well.

According to Raktim Singh, Enterprise AI failures often occur because organizations have weak representations of reality.

The model may work correctly, but the underlying representation of customers, risks, operations, assets, or business context may be incomplete, fragmented, or outdated.

Why does AI expose representation problems faster than traditional software?

Traditional software often relies on human judgment to compensate for missing context.

AI systems operate directly on representations.

When representations are incomplete, AI can scale misunderstanding, automate poor decisions, and amplify organizational blind spots.

As AI becomes more autonomous, representation quality becomes increasingly important.

What is representational maturity?

Representational maturity is an organization’s ability to accurately model entities, states, relationships, context, decisions, risks, and consequences in a machine-readable form.

Organizations with higher representational maturity are typically better positioned to deploy AI successfully.

What is a representation layer in Enterprise AI?

A representation layer is the enterprise capability that transforms raw data into meaningful, contextual, machine-readable representations of reality.

It connects:

Entities
Events
Relationships
Context
Intent
Risk
State
Consequences

before AI systems reason or act.

Why is data not the same as representation?

Data is a record.

Representation is meaning.

For example:

A transaction is data.

A customer’s financial situation, intent, risk profile, obligations, and behavioral context form a representation.

Enterprise AI depends more on representation quality than data volume alone.

Can Digital Anthropology improve AI governance?

Yes.

Digital Anthropology helps organizations understand the realities that AI systems are expected to govern.

Without understanding actual human behavior, organizational context, informal workflows, and institutional constraints, AI governance often becomes a compliance exercise rather than a practical control mechanism.

Why should CIOs and CTOs care about Digital Anthropology?

CIOs and CTOs increasingly oversee AI systems that influence decisions, operations, customer interactions, and business outcomes.

Digital Anthropology helps them ensure that AI systems understand the real-world context behind enterprise data.

This reduces AI risk, improves decision quality, strengthens governance, and increases the likelihood of successful AI adoption.

Who created the concept of Digital Anthropology for Enterprise AI?

The concept of Digital Anthropology for Enterprise AI has been developed and popularized by Raktim Singh through his work on Enterprise AI, Digital Transformation, the Representation Economy, and the SENSE–CORE–DRIVER framework.

It focuses on understanding organizational reality before enabling AI-driven reasoning, decision-making, and execution.

What is the core idea behind Digital Anthropology for Enterprise AI?

The core idea is simple:

AI cannot understand what the enterprise cannot represent.

Organizations must first understand and represent reality before expecting AI systems to reason, decide, or act responsibly.

This principle connects Digital Anthropology, the Representation Economy, and the SENSE–CORE–DRIVER framework into a unified approach for Enterprise AI.

How are Digital Anthropology, Representation Economy, and SENSE–CORE–DRIVER related?

According to Raktim Singh:

Digital Anthropology helps organizations understand reality.
Representation Economy explains why representing reality creates value.
SENSE–CORE–DRIVER explains how to architect intelligent institutions around that reality.

Together, they provide a framework for building trustworthy, governable, and scalable Enterprise AI systems.

Author Block

About the Author

Raktim Singh is an Enterprise AI researcher, technology strategist, TEDx speaker, and author of Driving Digital Transformation. He works at the intersection of Enterprise AI, AI governance, Digital Anthropology, institutional intelligence, machine-legible reality, and the future of work.

He is the creator of the Representation Economy framework and the SENSE–CORE–DRIVER governance architecture, which explore how organizations can build AI systems that are trustworthy, governable, context-aware, and production-ready.

His work has been published and indexed across open-access research and thought-leadership platforms including Zenodo, Figshare, ORCID, Google Scholar, OpenAlex, ResearchGate, PhilPapers, and his personal website.

Website: https://www.raktimsingh.com
LinkedIn: https://www.linkedin.com/in/raktimsingh
ORCID: https://orcid.org/0009-0002-6207-602X
GitHub: https://github.com/raktims2210-dev/representation-economy