The world’s views on drugs have changed dramatically over the years. Less than a century ago most currently illegal drugs were legal and used recreationally like marijuana and cocaine, and even medically in the case of many opiates, at the same time, the likes of LSD and ketamine didn’t even exist.

It was in the early half of the 20th century that people began demonizing drugs, an iconic example was the prohibition period across the USA. In this time period, it wasn’t just alcohol that was made illegal, marijuana was too, being labelled as a poison from as early as 1906. Things were only made worse with the country’s disastrous war on drugs beginning in the 70’s which by 2011 the Global Commission on Drug Policy declared “The global war on drugs has failed, with devastating consequences for individuals and societies around the world”. The war on drugs continues to this day, but in the last number of decades the world has eased up on drugs that aren’t tobacco & alcohol and this is evident with marijuana particularly being made legal in a new state every few years.


Taken from which itself has over 200 references for this data

Even just two decades ago this map looked extremely different, in 1996, 2 days before my birth, California just legalized medicinal marijuana.

It isn’t just marijuana that’s being considered for medical use. MDMA for example, better known as ecstasy, is known to help people with issues ranging from anxiety to PTSD.

Changing view on drugs isn’t however an international one, especially in the far east in countries like Japan & China, where drug laws are extremely strict, even in the futuristic smart city state of Singapore one can get the death penalty for smuggling in marijuana, and for carrying a few grams for personal use, which in Ireland where it is also illegal would get you a slap on the wrist and maybe a small fine, may land you in prison for decade.

It was this worldwide divide in people’s views on drugs that lead us to ask myself which drugs truly are dangerous and which ones aren’t? But which criteria defines whether a drug is dangerous? Dependency? Self-harm? Harm to others? We had to find out everything.


As we can see from this graph, marijuana appears to be the most common drug that adults on probation were under the influence of at the time of offense. However, we must take these figures with a grain of salt as a lot of questions still remain unanswered. Are these charges drug-related offenses, or separate crimes altogether that the suspect happened to be under the influence of while committing? Drowsiness and fatigue are common features one would have after taking cannabis, I find it hard to believe that anyone under the influence of this drug would have the energy or willpower in them to go off and commit any form theft or assault in any shape or form. For this reason in particular I believe that marijuana is the most popular on the list as a result of the suspects being caught in possession of the drug. Ganja is also known to have an incredibly strong and putrid odour, which would stop a lot of users from taking it indoors. Smoking marijuana outside leaves the users more open to being caught by the police then they would have if they were indoors. As well we must also take into account that marijuana might very well be the most common and accessible of these drugs, which would explain its popularity on the chart and the unpopularity of heroin. Figures and visualizations can only tell us so much. Context is crucial for each case for us to interoperate the circumstances of each scenario. This social graph makes it seem that people who smoke marijuana are violent, thuggish people which simply isn’t true. In any case, data can always be taken out of context to spread misinformed views if one wishes to push an agenda or if they are simply uninterested in the truth.


The two graphs above represents statistics compiled from Drugs and Crime Facts – US Department of Justice, Bureau of Justice Statistics. (

This graph visualises the percentages of former drug use of those caught driving while intoxicated. At first glance you instantly are led to believe that those driving under the influence of marijuana or hashish are the biggest problem on the roads, followed by cocaine, stimulants and so forth, but that is not what this graph is telling us. This graph represents prior drug use by DWI Offenders as opposed to stating what percentage of offenders were prosecuted while under the influence of the drugs listed above. The offender’s past use of drugs is unrelated to the conversation, this information is taken out of context and used to convey a motion that the majority of DWI offenders are under the influence of marijuana while driving.


The above graph is from Transport Canada – Road Safety in Canada. (

This graph represents the percentage of drug and alcohol positive cases according to age group. In contrast to the graph from the US Department of Justice, this graph compares the statistics of both drugs and alcohol positive cases, as opposed to solely identifying drugs as the issue with DWI cases. From looking at this graph, it is clear that alcohol poses a much greater risk in this case than drugs, especially with the younger demographic. As the age groups grow higher, we see that there are more drug-related cases, an explanation for which is thought to be the misuse of prescription or over the counter drugs such as valium or cold remedies by older people. Although the percentage of drug-related DWI cases is striking, the percentage of alcohol-related cases is far greater. However, the American statistics conveniently do not compare the drug and alcohol related cases and choose to focus on the prior use of drugs of DWI offenders. A reason for this may be the influence of the towering commercial enterprise that is the alcohol industry in America. In an attempt to ensure that people choose alcohol over drugs, drugs are demonised by using these statistics and examples of very specific cases out of context to provoke the idea that alcohol must be safer and less harmful. This is not to say that drugs are safe and unharmful, it just proves the point that data visualisation can be utilised to bend the truth for the benefit of those providing the information.

So when it comes to understanding what drugs are relatively safe and which are extremely dangerous and damaging what statistics can we trust? Can we trust statistics at all? We thought what if we looked at the potential of dependency of drugs, as well the lethal dose. The vertical axis shows how addictive the drug is, the horizontal axis is essentially how dangerous it is.


Gable, R. S. (2006). Acute toxicity of drugs versus regulatory status. In J. M. Fish (Ed.),Drugs and Society: U.S. Public Policy, pp.149-162, Lanham, MD: Rowman & Littlefield Publishers.

The data highlights how drugs like heroin, cocaine, and alcohol cause a high number of deaths a year while drugs like marijuana and LSD are practically impossible to overdose on. We can also see drugs like ketamine, which have an extremely bad name, is actually considered not too addictive, and seen as only a moderately dangerous drug, about on par with nicotine, which is one of the leading causes of preventable deaths in the world. So should this graph be your guide to which drugs are safe to take or not? Is it time to start popping tabs of acid and smoking rakes of weed? Well, not really. It’s true misleading charts is a good way to lie, as discussed extensively in the book How to Lie with Statistics by Darrel Huff where there is a whole chapter on how one can create a misleading chart by simply messing with the Y-axis. However this chart isn’t misleading, it shows exactly what it says – dependency and lethal dose ratios of each drug, but these criteria aren’t all that make a drug dangerous, and yet many drug advocate websites post statistics like these to show that drugs are fine for you. What this chart doesn’t show is how, for example, weed does impair a lot of people who smoke it, we know first-hand how it can induce the likes of anxiety and depression in certain people.


David Nutt, Leslie King, Lawrence Phillips, “Drug Harms in the UK: A Multicriteria Decision Analysis,” The Lancet, Nov. 1, 2010

So if not just lethal dose & dependence what statistic should we be looking at if we want to know which drugs are dangerous and which ones aren’t? Well, we discovered the truth is you shouldn’t be looking at any one thing for something as general as danger, and this is the best chart we could find, which compiles 16 different categories of ‘harm’ caused by each drug. Through this graph, we get both the total level of harm caused by taking each drug, along with what is specifically harmful about it.

It is unsurprising to see alcohol rated as the most harmful drug. While it’s high position may come down to it’s extremely frequent use and thus knowledge it is in my opinion undoubtedly dangerous – imagine ‘a night out on the lash’, hundreds of drunk people, fighting, screaming, yelling, crying, no other drug causes so much violence and mayhem, and yet we are so used to it.

In the middle were the likes of marijuana and ketamine, with no deaths occurring directly from these drugs, they were a couple of the few where the issues are mostly socioeconomic, and I wonder if once made legal & socially acceptable the harmfulness meter would go down.

LSD overall is still ranked amongst the safest drugs to take, as it has been in all the data we have used so far, what this new data shows us is that whilst overall it is relatively safe, when it comes to impairment of mental functioning it ranks as high as crack-cocaine, and that’s the kind of thing people need to look into when considering taking these kinds of drugs – there is more ways to be harmed by drugs than crime, addiction, and overdosing.

To conclude; data doesn’t lie, people do, data doesn’t misinterpret itself, people misinterpret data. Stay vigilant out there in this dark-age of misinformation on the net.


The Rise of the Digital Scientist

I love computers and multimedia, it’s what I do, but there’s a lot more things I’m interested in that I don’t necessarily get to delve into in my free time. Ecology, astronomy, and history, are all things I don’t get a chance to study in college, nor are they things I was exceptional in back in secondary school, but I am none the less extremely fascinated by them – this is where being a citizen scientist comes in.

Citizen science by its most basic definition is public participation in scientific research – it takes many different forms ranging from stargazing to butterfly catching to transcribing. The one I have come to have direct experience with is known as Zooniverse.

The fine lads & lassies of the Cascades Butterfly Citizen Science Team – Sauk Mountain

Zooniverse is a website for citizen scientists operated by the Citizen Science Alliance. It is home to some of the world’s biggest, most successful, and most popular projects to do with citizen science.

The site focuses on many different kinds of projects, initially I planned on helping with a project under the languages category, after all I’m studying – and failing – Spanish, but when there was nothing there to work on I let out a sigh of relief and delved into something I’m really interested in – nature. My fascination with nature comes not from years playing in my back garden which teaming with wild-life but from watching too many David Attenborough documentaries & successfully getting an A2 I leaving cert biology.

The first project I helped with was called ‘Mapping Change’. The project imagines a public atlas, which is searchable, showing where plants, fungi, and animals have been found & collected. The map focuses across many different American ecosystems in the midwest, and also represents moments in history before key changes occurred to the environment, climate, and landscape, notably from extensive European settlement at the time.

My job was to transcribe the data from hand-written museum specimen labels to map biodiversity. I had to note if there was more than a single primary label present, I then had to draw a rectangle around the primary label to tag it, and finally I transcribed the scientific name of the plant, the collectors name and number, and date of collection from said label, I did this for just over a dozen plants.

The process might sound a bit boring, but I found it quite interesting. Because I’m interested in botany it was just cool to just see these preserved pieces in the first place, they are from a natural history museum after all. I also learned how far data preservation techniques have come, there are some plants labels from the 1800s and they would always be in scrawled handwriting, missing certain things, difficult to discern, and tended to contain misspellings more frequently, compared to many from around the 1950s, which are almost always perfect with their primary labels being written with a typewriter, and then there were some from as recently as the 90’s that were printed from a computer and had a larger wealth of information about each plant than anything prior.

1903 – 1952 – 1990

I felt like I was doing something important, and that may also have been part of the fun. This is work that takes beyond nothing for me to do and will go on to benefit people for a long time, even if it’s in a minute way, that’s why after an hour or so working on it I felt like I hadn’t lost any time.

While I can’t imagine using data of these old plants myself in any of my work I found it enjoyable from both a historical and an ecological perspective, and the fact that it’s going to be mapped ticks a third box of buzz for me, because I love me some maps.

The transcribing itself was good practice for preserving & managing data. It gave me an idea of the kinds of challenges I may stumble upon, such as hard-to-read handwriting and difficult to understand misspellings, on top of that as I mentioned it really showed me how far we’ve come in preserving information. The project also gave me ideas on how I might display things through time on a map, something I struggled with using Google MyMaps when I created my digital artefact.

I did over a dozen of these before pouncing on to a new project ‘Camera CATalogue’. Every year, Panthera’s motion-activated cameras collect hundreds of thousands of wildlife images.

It became my job to analyse these photos to identify the animals shown, letting them track wild cat population trends over time and determine what conservation actions are needed to better protect them.

A spooky spotted hyena that I stumbled upon

The first thing you’re greeted with is a random image that was triggered by the cameras I mentioned, along with a list of animals to the right

I found this interesting as it was a similar project in the sense that they were both about preserving and understanding nature but it was so different in that I was looking at live, recent specimen, and I was tagging what they were myself, rather than just transcribing what someone had written decades ago.


On the right-hand side of the photo that I was inspecting was a list of 50 animals, along with 4 more options that may have triggered the camera that did indeed pop up a few times (human, fire, vehicle, nothing).

Now I’m no expert on wild animals in Angola or South Africa, but the project was so user-friendly and required nothing but clicking on my part. When I assumed it was a spotted hyena it just asked me how many were in the photo, which side of the animal was faced towards me, and what I would rate the picture! There were a couple of cool things in this project that I found really helpful – the sample image of that type of animal, as seen on the image there, allowed me to compare images to make sure I had chosen the right animal, but the ‘often confused  with’ section, which showed animals that frequently get confused with one another, was even better, especially when it came to differentiating the four or five different type of deer-like animals, as I reckon most of us don’t know the difference between a Reedbok, an Impala,  and a Steenbok.

I found this whole project quite exciting as I had just finished transcribing these primary tags from old plants and now I was in a sense creating these primary tags myself! I ended up doing over 50 of these

I actually had a great time doing it because it was easy, fun, exciting, and most of all I knew it was helping – more so than my transcribing project. While my transcribing will go on to help future botanists and other plant folk there was a sense of truly helping endangered animals here as ultimately their goal is to determine what conservation actions are needed to better protect these species that I would label, notably the cats. I’ve also learned to appreciate nature that bit more, from seeing these animals just hanging out.

The user interface is what I find truly fantastic. When I think of people categorising animals I don’t think of them doing it so intuitively, it sounds painstaking, slow, and as if it requires prior knowledge, the emphasis on preview images for animals and an ‘often confused with’ section as I mentioned is so minute but something that made it so much better. These simple bits of instinctive and helpful GUI can go a long way when it comes to submitting information and I’m definitely inspired.

I wrapped up my time on Zooniverse doing a couple more projects but there wasn’t much new I gathered from either – one was ‘Focus on Wildlife Cleveland Metro Park Statistics’. This project was nearly identical to the project I just wrote about, except that instead of tagging animals across Africa I was mostly just tagging woodland creatures in some of Ohio’s extensive nature preserves. I enjoyed working on it as it hit a bit close to home, being in temperate woodlands like Ireland, as opposed to the hot African desert, it felt like I was peeking in at animals that are all around us right now, it has me wishing I was in the scouts looking for beasts in the woods.

A super sneaky deer trying to spook me

Something quite intuitive that I noticed was that it didn’t just take a simple still image but actually took a burst of 3 across a small space of time that you could cycle through or play like an animated gif – this was fantastic as in a lot of the African pictures I would see just the butt of an animal, not enough to discern what it was, with the multiple frames I would frequently see an animal hop fully into the second or third frame.

Finally I spent a small bit of time on ‘Arizona BatWatch’ purely out of curiosity as I spent a lot of time in Arizona and bats are just pretty cool dudes.

Zooniverse is batsh*t crazy

All I had to do was watch a 20-second clip, discern how many bats were on screen at any given time and simply mark what behaviours I saw from a small list – e.g. flying inside, outside, bumping. In the space of 15-minutes, I did around a dozen,  and it helped scientists learn about the behaviour of these bats!

It was the only project I did that focused on the subject’s behaviour and not just it’s existence or basic properties, the fact that I could slow down time in the video, as slow as 25% of the original speed, helped a lot, in fact it was a necessity watching something as sporatic as a bat. For me this highlighted how much more we can understand with digital tools – there’s no way someone could know some of these bats habits without being able to slow down time like I can now.

These last two projects cemented the idea that when it comes to us as humans interpreting visual information video tends to work to best over images – even in some cases such as with the bats when the video is of a far inferior quality it was easier for me to understand what’s going on more than if I stared at a HD colorized image. I will definitely be taking this into account with my work in the future.

After my time on Zooniverse I feel like doing some citizen scientist work should be mandatory for students young & old, to bring humanitarian and scientific issues into their life while also giving them something to work on and a whole world to appreciate. I’ve also been inspired by the projects frequently simple and intuitive GUI, which will definitely help when it comes to my projects in digital curation & data management.

Say Goodbye To Waiting In Line

What if we could create a shopping experience with no lines and no checkout? This is what Amazon was asking itself when it started development on a little thing called Amazon Go four years ago. Here’s the lowdown.

I wrote a little piece here on how robots are capable of even replacing us when it comes to creative writing, so it’s no surprise to see robots replacing more menial jobs.

How are they going to do it? Amazon says by pushing the boundaries of machine learning, sensor fusion, computer vision, and a bunch of other technological mumbojumbo, they will create a store where people can just pick up stuff and go. Put simply their new tech can detect when products are taken from or returned to the shelves and keep track of them in a virtual cart. Shortly after leaving the store your Amazon account will be charged and a receipt sent to you.

All one will need is an Amazon account and the free app (and a phone that can run it). Amazon Go will be the name of app, whilst Just Walk Out Shopping seems to be the name of technology behind it all.

The first Amazon store fitted with this technology has already technically opened in my birthplace – Seattle, Washington! At the moment it’s exclusively open to Amazon employees, but it’s due to open to the public in 2017.

Seems flashy enough

Of course some of the internet has already erupted in techno-phobic hysteria due to possibility of more job losses, despite the fact that new technology will create new and different kinds of jobs and more importantly even the majority of people working in retail are simply not happy in retail, at least not behind a cash register at a grocery store working for minimum wage.

I reckon it will be many years before we see this technology in the big-name supermarkets, but hell maybe with this new technology Amazon Go will come to even replace the likes of Walmart in the US and become a big name supermarket, regardless, it will surely make our lives just that bit more convenient and change the lives of the countless people who are misemployed, allowing them to do more valuable things, for themselves and society, as opposed to the operation of a cash register – even if it’s working exclusively on the store-floor of the same grocery store talking to & helping customers – it’s more rewarding than having the job of an automaton.

Writers Aren’t Safe From The Rise of A.I.

More and more people are being displaced from their careers every day, mostly simple jobs like cashiers and factory workers, but it begs the question, will robots eventually take all of our jobs?

We like to think of the arts especially as a bastion of humanity, whereby no matter what jobs computers take over that a machine on its own will never produce decent pieces of literature or art, but we’re slowly coming to the realization that this isn’t the case. Simple twitter bots, for example, are creating little stories all the time.

One bot, in particular, that’s quite close to my heart is a tiny twitter bot created casually by two people, BuzzFeed writer Chris Rodley and Teacher & Coder Yeldora  that ‘writes a magic story every two hours’, its name? Magic Realism Bot. But how does it work? Below is just a little glance the little bots thinking process.

The tweets it produces range from surreal and intriguing…

…to just pure hilarious

It’s by no means the first twitter account of it’s kind. The twitterbot craze began as early as 2010, most notably the endearing Horse_ebooks, which created tweets from jumbled sentences from horse training e-books.

There are countless other funny & cool bots out there, such as dronesweetie that takes photos of drones from google images and attempts to describe what it sees, and even a couple spooky ones, like FFD8FFDB that tweets random still images from a list of unsecured webcams.

Even if we ignore rapid advancements of A.I. with extremely complex algorithms, and look at what tiny bots are doing on social media we can begin to grasp what kind of stories machines are capable of weaving.

How Memes Have Hijacked Your Mind

We all love a good meme, almost anything funny on the internet is considered a bit of a meme these days, but memes in general have been evolving lately – in both their complexity and in their meaning. But what exactly is a meme?

Meme: an image, video, piece of text, etc., typically humorous in nature, that is copied and spread rapidly by Internet users, often with slight variations.

Remember this little bastard?

From infamous simple gifs and lolcats, to copypastas and advice animals, to the pepes, the rare pepes, and the trump pepes, memes have seen a lot of developments and changes over the last decade. What started as mere jokes on the internet have changed into something entirely other.

Memes have become powerful tools to convey emotions, and beliefs – take Christian Memes on facebook, a gigantic page that has millions of followers and gets thousands of likes on each post, unironically I may add.
These images range from teaching bible stories to simply reinforcing ideas of what it means to be true Christian, all in a relatable, recognizable, and ‘funny’ fashion (that is if you have the sense of humour of a boiled egg).

It’s not just Christian Memes – There are massive Athiest meme pages too, where snarky Atheists  reinforce their beliefs and ideas with each other in a comedic fashion

Memes are so effective at getting beliefs, thoughts, and emotions across that most of us have entire conversations using nothing but them, so maybe it’s not surprising to see facebook groups revolve around them conveying more serious ideas.

We don’t just use memes with each other though – they’re being used ON US to get us to buy products or to sway us a certain way – one can’t deny that the act of dabbing on TV and memeing on twitter won Hillary Clinton plenty of millennial voters. My friend Luke wrote a post about Pepe the Frog and how he went from old meme to a symbol for neo-nationalism and declared a hate symbol by Hillary Clinton’s team, read about that here.

Emoji Empress

Memes are so effective at hijacking our mind because they’re familiar and they rely on us to share them – when a politician or an establishment uses emojis or posts a meme it’s a cheap way of relating to us on the net, and by neptune it works, it works so hard that we’re all willing to retweet it and share it on our own pages as if we’re all little unpaid marketers, passing the meme and all that comes with it to our own followers.

Ultimately memes are still used as they always have been – as a joke, a reaction, an opinion – what’s changed is their complexity and power. Memes have become more than just funnies; they are funnies with the ability to change how we think and act.

A Visual Analysis – V.G. Boards

The time has come to do my end of year digital humanities assignment – to analyze any publicly available text using some visualization tools such as Voyant 2.0 or RAW. Mere hours before the deadline was spent procrastinating wondering what to do, I didn’t even know where to begin, so there I was wasting my life away as usual on 4chan’s infamous video game imageboard, ‘/v/’, when I thought myself, why not do a textual analysis on an average thread here, and so I did. I clicked in to a thread on Dark Souls 3, a recently released video game from a series famous in large part due to its frustrating difficulty and addicting gameplay, I chose this thread as it was one of the first threads I saw, it had hundreds of replies, and because Dark Souls is relevant right now – the thread began with “I can’t take this anymore – “I CAN’T F*CKING TAKE THIS ANYMORE”


I used Voyant-Tools a fantastic free online tool that lets you get a visual of the most used words in a block of text. What I did was copy 20 of the first replies in the thread and 20 of the latest, and these words above were most frequently used. The words don’t just reflect on the tough, infuriating nature of the game, but also on the community on /v/ – one that is known to be wonderfully toxic, and where anything goes. Two of the most used words are ‘F*cking’ and ‘F*ck’, the whole thread quickly became a thread about ‘PvP’ – Player Versus Player combat, hence the words ‘people’, ‘invasion’, ‘host’ etc. which reflects the competitive nature of users on /v/ The lack of anything really positive reflects /v/ users attitude on games, it is a community that largely comes across as extremely arrogant and nitpicky  complaining about the game being difficult, telling them to ‘f*ck off’ and ‘git gud’. There appears to be no correlation between simple ‘fun’ and playing ‘games’ to the average /v/ user as my data visualization displays, as would any visit to the board.

But gamers online are notoriously toxic anyway, the most stereotypical view of a gamer, even within the gaming world, is that of an obnoxious 12 year old shouting racial slurs through his headset, so I thought I’d compare it to another website that has a very large video game board, reddit, specifically ‘r/games’, and once again I picked the first Dark Souls 3 thread I could find, copy and pasted a bunch of posts in to Voyant, and here are the results:

 darksouls3 - reddit

The difference is definitely interesting, but also just as I expected. The most used words reflect the game itself – ‘dark’, ‘bloodborne’, ‘game, and ‘souls’ referring to the games franchise itself, and you can see there’s proper general discussion going on about the game – from talking about ‘levels’, ‘knight’, ‘area’, ‘boss’ etc.

What is this difference down to? Despite the visual data and what I’ve discussed it may not simply just be that it’s a different community that happens to consist of more toxic people, in fact I know for a lot of users who overlap with both boards, especially when it comes to a game that originally began with a cult following like Dark Souls.

I think it genuinely comes down to anonymity overall. On reddit you make an account, everyone can see your username, what you comment, when and who you follow etc, and you’re there in the first place to have proper discussions, you may also risk the possibility of getting your account suspended or banned for various reasons. By contrast users, including ones from reddit, come to 4chan’s /v/ board and use it as an outlet as it offers anonymity, you can say anything you want and no one knows nor do they care who you are, you spout ridiculous crap, something deemed illogical, or an opinion that is unpopular, it’s a place to argue with strangers, complain about a game you wasted money on, or yell in to the empty void that is the board about how video games ruined your life and now don’t have any friends.

Ultimately visualizations like this can’t tell the full extent of what’s going on in large clumps of text, whether it’s movie scripts, books, or internet threads, however it certainly helps us understand what is happening at their core.