HERSTORY MILESTONES: WOMEN'S PARTICIPATION IN UK POLITICS

WORDS BY IZZIE ADDISON IMAGE BY FLOSSY WATERS

The 2019 General Election saw a recordbreaking 220 women elected to be Members of Parliament. The first woman MP to take her seat, Nancy Astor, was elected one hundred years before this in 1919. So, how did we get from Nancy Astor to Theresa May, with the gender divide in the Commons ever-decreasing? What work is still to be done? Here’s the journey of women in UK politics tracked through some key milestones from the past 100 years. 1918: The Representation of the People Act and The Parliament (Qualification of Women) Act

Though many still consider 1918 to be when women got the vote in Britain, enfranchisement was only extended to women aged over 30 who could meet a property requirement, or whose husband could.

Passed the same year, the Qualification of Women Act enabled women to stand for election to Parliament - provided they were over 21 years old. The first woman to be elected as an MP was Constance Markievicz, for the Sinn Féin party, but she did not take her seat, having refused to take an oath of allegiance to the king.

This American-born politician was also the first woman to pass a Private Members’ Bill in the House of Commons. A candidate for the Union party (now the Conservative Party), Astor was responsible for prohibiting the sale of alcohol to those under 18. Battling heckling in the Commons and conspicuous sexism, Astor supported any other women MPs regardless of their party and argued for health and social care reform. It was certainly an uphill climb for Astor, who found some other MPs would refuse to talk to her, and was told by Winston Churchill that they hoped to ‘freeze her out’.

1928: The Equal Franchise Act

This Act gave all women equal voting rights to men - those aged over 21 years old could now vote, and many did so for the first time in the general election of 1929.

1929: Margaret Bonfield becomes the First Woman to be a Cabinet Minister

Bondfield was made Minister of Labour for the Labour government, after previously being the Parliamentary Secretary to this role. Like Astor, Bondfield greatly influenced women’s rights and worked throughout her career to progress towards gender equality and universal suffrage.

1958: First Women in the House of Lords

By this point, women had been allowed to stand for election to the House of Commons for forty years, but excluded from the House of Lords. 1958 saw four women elected as life peers alongside ten men. It was not until 1963, however, that women were allowed to become hereditary peers.

1975: Maureen Colquhoun Becomes the First Openly Gay Woman MP

The Daily Mail reported that Colquhoun had moved in with a female partner, a headline which the MP took in her stride - she would not apologise for her sexuality or her opinions. Sadly, this had a negative impact on Colquhoun’s public support and she lost her seat at the next general election.

1979: Margaret Thatcher becomes the First Woman Prime Minister

The controversial Margaret Thatcher divided feminists when she became the first woman MP to lead but seemingly sidelined all others during her eleven-year tenure.

1987: Diane Abbott becomes the First Black Woman to be elected as an MP

Still a famous political figure serving today, Labour’s Diane Abbott was the first Black woman to be elected as an MP. She has served in the same constituency she was first elected in, Hackney North and Stoke Newington, uninterrupted ever since.

1992: Betty Boothroyd becomes the First Woman Speaker of the House of Commons

Still the only woman to serve as Speaker, Boothroyd is an ex-Labour MP who served as Speaker for eight years, being praised by ex-Prime Minister John Major as ‘outstanding’ in the role.

1997: A Record Number of Women MPs are Elected under New Labour

Nicknamed ‘Blair’s Babes’ by the media - coined, of course, by the Daily Mail - Tony Blair’s first general election win in 1997 saw the election of 101 women MPs to New Labour - it was, back then, the highest number ever elected.

2016: Theresa May becomes the Second Woman Prime Minister

Conservative MP Theresa May became Britain’s second woman Prime Minister in 2016 and served until she stepped down in 2019. It is perhaps unsurprising that May has been compared to Margaret Thatcher - Jacob ReesMogg explicitly encouraged May to draw inspiration from Thatcher when she hashed out her Brexit strategy and leadership style.

While we have gone a long way from the hostility Nancy Astor faced, women at the top are still lumped together in the same sparsely populated category regardless of their differences, and measured against one another as opposed to other, male Prime Ministers. But if we are to progress with the way we think about women in politics, they need to be judged on an individual basis too - a right we have always given to men.

Man & Machine:

Next-Step Evolution or Dystopia In Waiting?

There's a certain milestone that feels attached to bionics. In the landscape of evolution, humans seem to be one of the quickest species to evolve, as natural selection's "survival of the fittest" becomes more obsolete as a wider catalogue of genetic traits and differences breed themselves into society. As Gregory Cochran and Henry Harpending argued, human evolution is happening around 100 times faster than when it first started, but whether true or not, a new question begs to be answered: is bionics the next step in human evolution?

Bionics, cyber-enhancements, cyberpunk aesthetics, etc., all borrow from the idea of the integration of man and machine. It's a sub-genre of literature that feels very much grounded in the technical fiction of the late 1940s and early 1950s, no doubt inspired by the technology boom that happened during the time. From there on, it grew in relevance, becoming a huge section of science-fiction as its roots spread into films like Blade Runner and RoboCop. Yet, man and machine feel less like fiction every day as we begin to question how we can augment the human body with machines and bionics. The pacemaker is already an excellent example of how technology can be used to enhance the human condition, but for the most part humans and technology only tend to become integrated when it serves a purpose like saving one's life.

When we begin to move past the stratosphere of life-saving technology, the place for bionics quickly fades for most people. However, if we think about the bionics and techenthusiasts who are currently working in the sector, one name often sticks out: Elon Musk. The tech giant largely behind the success of Tesla is at the forefront of human bionics, most notably with his brain chip, Neuralink.

Neuralink is currently in the animal-testing phase and is in no shape the huge leap in bionics that we are sometimes led to believe. Neuralink won't let you stream music to your brain, open doors by thinking about it, or let you stream thoughts to someone else's Neuralink. As stated on the website, the initial goal of the technology is 'to help people with paralysis to regain independence through the control of computers and mobile devices'. In a way, it serves the same medical functionality that the pacemaker was designed to serve - they're both designed to be medical devices. However, how the Neuralink differs from the pacemaker (apart from one being attached to your brain, and the other to your heart) is its ability to be expanded upon. While Neuralink currently exists as a potential medical device, that doesn't mean it will always be the case.

The possibilities for Neuralink, if ever successfully moving onto human trials and working, is practically endless. If the technology ever proves successful, it doesn't only represent a quantum leap in our interaction with technology but it also represents a greater understanding of neurophysics, neurobiology, neurophysiology and even neuropsychology. To integrate arguably our most complicated organ with technology could be seen as an epitome of bionics, and the fact that Neuralink seeks to accomplish that even before any other breakthrough in bionics (apart from inserting tiny microchips into our flesh to unlock doors) is quite astounding. Neuralink is a technology that seems to have endless possibilities, but with those possibilities, comes endless fears.

There's a reason cyberfiction often comes attached to dystopia: endless possibilities are open to both good and bad interpretations. While Neuralink seeks to help those with paralysis re-establish their independence, could it be reverse engineered or tampered with to maliciously hurt someone? Could Neuralink cause the breakdown of human interaction and communication, as it forces the world even closer to an exclusively technological, dare I say, metaverse? It all sounds like fearmongering speculation, but in technology as new and undetermined as Neuralink, speculation is all we have and know. As history shows us, just because something is invented with good intentions, doesn't mean it's never exploited for the opposite.

Yet, there's a feeling of evolution attached to bionics. In a world that becomes increasingly reliant on technology to accomplish the most mundane of tasks for us, biological evolution seems less necessary. As the years pass by, it's less about how humans can evolve to better suit the environment and more about how we can evolve the technology to make the environment better suit ourselves. As Neuralink represents, perhaps one day the evolution of technology and biology won't be separated but instead integrated. Maybe one day, the next step in human evolution will be the newest piece of technology that sits on the market for consumerists to purchase. Whatever happens though, for good or bad, a technological world has an eerie shadow of a dystopian-world lurking in the background.

WORDS BY SAM PEGG IMAGE BY REN NEOH

Why Development of Self-Driving Cars is Stuck in the Slow Lane

WORDS BY BARNEY WHIFFIN IMAGE BY JULIEN TROMEUR via PIXABAY

1.35 million people die every year on the world’s

roads. Bit peak. Since the dawn of the automobile, attempts to reduce the number of road deaths have included mandatory driving tests and mandatory safety features in cars. However, a fundamentally different approach is required. In a 2011 survey showcasing a stunning example of illusory superiority, less than 1% of drivers considered themselves to have below average driving ability. Clearly, the problem here is rooted in allowing people to drive at all.

And there are more issues than just the death rate. Traffic is annoying and costly, and the main cause is often cars failing to pull away in unison after slowing down/stopping. There is also the financial problem. In the UK, the average used car price is £19,250, while the average salary is only £25,750 (and I’m generously ignoring new cars here). Clearly, a better solution would be to move away from private ownership of cars and head towards a world of cheap, autonomous taxis.

There are a few problems holding up the development of self-driving. These include creating the technology which enables it, passing legislation which allows for the tech to be used on the road, and answering moral questions about the decisions these cars can make. There have been a few approaches made to solve the first problem. The most popular of these involves LiDAR (Light Detection And Ranging), which uses lasers reflecting off the surroundings to generate a 3D map of the area, and to work out if the car is about to collide with something. The main problem with LiDAR is that the most popular sensor, produced by Velodyne, costs around $8,000, making it next to impossible to use in an affordable car. Cheaper sensors are available, but their reduced accuracy results in unsafe driving at highway speeds. Another issue is that LiDAR is inherently unable to read road signs, or road markings.

As cars and roads were designed with human vision in mind, a vision-based approach makes more sense. Tesla and other companies are working on self-driving using cameras, coupled with some affordable sensors. This is much cheaper than LiDAR, and allows for cars to learn object recognition, and to read traffic lights and signs etc. The challenge here is rooted in the software for interpreting the information from the sensors, essentially an AI which learns how to drive. This requires deep learning, which in turn requires huge datasets. This is where Tesla has a large advantage over the competition, as they have 3 billion miles of real-world autopilot data (autopilot is simpler than full self-driving, but the data is still highly valuable). Other companies are relying solely on simulation data, which is cheaper and easier to make progress with, but is less likely to ‘surprise’ the AI (a requirement to avoid overfitting and ensure thorough safety).

Another approach is to use C-ITS (Co-operative Intelligent Transport Systems). This means focussing not on the car, but on self-driving through communication with the driving environment. For example, construction cones that tell the car where the construction area and temporary lanes are. This would also involve smart traffic lights and communication from car to car. C-ITS is a good idea, as it greatly reduces the dependency of each individual car to learn how to drive, but it suffers in that every road would require installation of smart driving features. This would be an expensive and lengthy process.

Tesla has the lead on self-driving technology, but its progress has been held up legally. Teslas on autopilot have 1 crash every 4.3 million miles, compared to 1 in every 0.5 million for other cars. However, every time a Tesla on autopilot crashes, it makes the news. This suggests that many people have strong feelings about allowing selfdriving cars on the road, and these feelings are reinforced by the legislation. The general argument being made is that self-driving cars need to prove themselves to be safe before they can be tested on the road and potentially risk human lives. But this is seriously holding up progress (and the same argument is not made for human learners). There are also legal issues with liability, insurance, privacy, cybersecurity & ransomware, all of which will need tackling.

Another problem is moral decisions. The classic example is a scenario where self-driving cars must choose between killing a pedestrian or a passenger. A 2016 paper on the social dilemma of autonomous vehicles found, rather perplexingly, that people wanted self-driving cars to value pedestrians over passengers, but that they would not buy self-driving cars programmed this way. Another complication is that global surveys of millions of people (answering this and similar questions) suggest that ethics vary from country to country, and so self-driving ethics must adapt accordingly. However, it is worth noting that scenarios such as a choice between murders are incredibly rare, with critics suggesting that it is akin to worrying about how a self-driving car will deal with an asteroid So, there are a multitude of problems, some of which will be overcome with time, and some which require a tremendous effort of engineering. But self-driving cars are coming. They’re just stuck in traffic hehehe.