Sometimes the findings made in molecular biology seem like countless, tiny pieces of an enormous jigsaw puzzle: some of them we have managed to connect together, forming little islands of knowledge, but they are overall so far apart that we cannot make out what the entire picture is supposed to look like.

"Flowers" produced by successive generations growing in complexity, carrying different mutations of primordial flower shapes (Source).

The analytic and reductionist approach has brought a lot of success to modern biology, especially at molecular level, chopping things into ever smaller slices. Still, I have to confess that I often feel like I am sinking in a pit of despair smothered by terabytes of scientific data that has been produced by countless research groups doing nothing more than just piling up and sitting stored somewhere without anyone truly knowing what it means. The hot thing to do nowadays is to produce “big data” and obtain an ocean of information on everything, from a single cell to a cancerous tumor.

However, is this really getting us any closer to actually understanding the biology of it? The current state of affairs with science seems to call for an urgent unification and interpretation of all the information produced in the last few decades.

This is not the only approach, and people have been venturing into alternative pursues for the clarification of these biological mysteries for an embarrassingly long time already; the thing is, not many people seem to really care about what they want to say.

In 1987, Chris Langton and a small group of hardcore computer, philosophy and biology geeks gathered in what came to be the first conference on Artificial Life, a newly emerged discipline that started to produce promising advances on the unraveling of the hidden facts of the nature of life on Earth.

Such achievements included computer programs that reproduced the behavior of flocks and schools of fish, models portraying the emergence and evolution of life, cellular automatons and little virtual organisms that adapted within their simulated ecosystems.

An example of flocking behavior generated in silico (source).

An example of a cellular automaton: CONWAY’S GAME OF LIFE

In 1970, mathematician John Horton Conway devised a game called “Life”. Such game could be played in a simple checkered board (like a chess board) using a few pieces. Each square on the board symbolizes a cell and can be either “full” (when a piece is in it) or “empty”.

In the board, each cell has eight neighboring cells (the surrounding squares on the board). The game starts by placing the pieces in the squares in a chosen initial position; then, the game progresses step by step, with each individual step determining the state of the next one by using the following rules:

1) An empty cell will become full if three of its neighbors are full.

2) A full cell remains so if two or three of its neighbors are full, otherwise it becomes empty.

In this way, the state of the neighboring cells is accounted for each cell, and the rules stated above determine what the state of each cell will be in the next generation. By doing this repeatedly, interesting patterns begin to emerge, depending on the initial position chosen; sometimes the game dies down quickly, and sometimes the game fluctuates or stagnates due to cells being isolated and clustered together.

An example of what the "Life" game can look like (source).

In fact lots of crazy and unexpected patterns obtained by playing this game have been documented, some of them are pretty impressive and really look like a living system. People actually became addicted to playing this game in computers (mind you, it was the late 70's/early 80's). You can see some really cool examples of these life-like behaviors here.

One of the most powerful tools that artificial life provides is its holistic perspective and wholesome way of solving problems. One of the biggest goals of artificial life is to achieve the synthesis of life, or at the very least achieving a simulation that is very close in function to a living system.

However, to successfully accomplish this, artificial life must make use of the immense wealth of data about living organisms that modern biology has managed to accrue until now. Before we study the interactions and relations between the different parts of the whole, we still need to know the components and the individual functioning of each part. Hence, the knowledge obtained in a highly specialized and reductionist way is still incredibly valuable! It will become building blocks for more complex and sophisticated systems.

Of course, we also need to have at least a general idea of what life is in order to be able to synthesize it in the computer. One of the advantages offered by artificial life is the lack of prejudice about the way in which life can be represented; many people argue about whether such computer-based entities can truly be considered “alive”, or if life can be built with different materials to those that form the living forms we are already familiar with. This is the point where proponents of Artificial Life usually fall into one of two factions:

The “hard” one, that claims that the organisms generated in the computer are indeed autonomous living beings subject to evolution (according to this posture, Conway’s game of life could be considered a legit living system), and
The “soft” one –which we could say it’s the most politically correct one and won’t cause anyone’s monocle to be dropped in outrage– which supports that such computer creations are highly sophisticated simulations of the real phenomenon that is life.

Would you consider something like this "alive" on its own right? (source).

Going even further, one could argue that depending on the level we look at, things can appear more or less alive. All living beings are composed by the same atoms, which in turn are composed by electrons and particles in constant agitation, therefore in a sense we could say that true death would be the complete cessation of such movement– a radical notion already proposed by Mexican biologist Alfonso Herrera in 1904.

Building into this idea is the concept of autopoiesis (literally “autoproduction”), which was a property proposed by biologist Humberto Maturana as the fundamental distinction between the living and the non-living. Autopoiesis refers to the network of self-organization and production within a living unit (a cell, for example), in which the products of the processes within the network help to maintain it while simultaneously being part of it.

Working with the concept of autopoiesis in computer simulations has allowed to cast some light into other interesting philosophical problems about the nature of life, one of them being emergence.

Emergence the fascinating property of life that makes the whole into much more than the sum of its parts. The apparent contradiction regarding emergence lies in that emergent phenomena in living organisms are at the same time autonomous and dependent from the basic processes that conform them. In other words, how can we consider something as autonomous, when it is dependent on its basic phenomena or processes?

Artificial life can help us find an answer for this question. In it, we can see that such emergent properties do not arise in an unexplained or metaphysical way, but as a result of countless interactions on a “micro-level”, the consequences of which reverberate into the “macro-level” or the observable level, exhibiting behaviors that were not expected when only taking into account the initial components.

From the point of view of artificial life, then, a property that is considered as emergent in a system must be a result of the dynamic interactions within such system in a micro-level, as the result of processes like iteration and aggregation of components. In this way, we can start taking a peek behind the veil of how life originates!

Fun facts about the history of artificial life:

Through decades of research and speculation by some of the most imaginative minds in science, the development of artificial life systems has produced some truly fantastic episodes:

There are several examples of people attempting to "animate" machines dating back as far as the 18th century. One of these examples is the mechanical duck created by some Jacques de Vaucanson in 1735. The mechanical animal used to tour around like an attraction, and reports state that it moved in a way that conveyed autonomy, and more surprisingly it was capable of eating food and digesting it –all the way to the last step!

The decaying remains of the mechanical duck, after it resurfaced in the mid 19th century.

In 1980, a very out-of-the-box team sponsored by NASA came up with the idea of producing self-replicating lunar factories that would be used for space colonization and exploration of mineral resources within the solar system and beyond. The idea was that such systems would be able to produce their own components, copy themselves and proliferate. An extensive discussion on the project was done (including the potential threat to humankind of having such "living" factories invading the universe), but the project was never realized.

(Source).

Computer-generated swarm intelligence has been applied not only for scientific purposes, but also for entertainment. A famous example of this, was the use of such algorithms to animate the computer-generated armies for the war scenes in the Lord of the Rings films!

Hope you found this interesting! Do not hesitate to share your ideas in the comment section...

Cheers,

Irime

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References:

Emmeche, Claus. 1994, The garden in the machine: the emerging science of artificial life. Princeton University Press.
Levy, Steven. 1992. Artificial Life: The quest for a new creation. Penguin Books.
The Ontological Status of Artificial Life