0:00:01.140,0:00:05.220 Thank you very much for this introduction, Greg, it's a great pleasure for me to be here. 0:00:07.080,0:00:11.280 And the person you see on my slide is Masako Wakamiya, 0:00:11.280,0:00:15.540 she is an app developer. She was born in 1935 and 0:00:15.540,0:00:21.120 built her very first app when she was 82. And on the right you see this app it's 0:00:21.120,0:00:27.720 called Hinedan and for a Japanese members in the audience I need to apologize for my pronunciation, 0:00:27.720,0:00:34.200 but this is essentially a game which is training kids to prepare an altar for a girls' festival 0:00:34.200,0:00:37.920 called Hinamatsuri. And you need to put 0:00:37.920,0:00:42.360 those dolls in the right places. So she is of course exceptional, 0:00:42.360,0:00:46.920 but there are quite some older software developers who are around, 0:00:46.920,0:00:52.800 and previous studies have shown that the programmer reputation scores on Stack 0:00:52.800,0:00:58.140 Overflow tends to increase well into the 50s, and there is no strong correlation between 0:00:58.140,0:01:04.440 age and scores and specific knowledge areas. So this is what - essentially suggests that older 0:01:04.440,0:01:10.380 software developers should thrive in our world. But at the same time Quora is full of questions. 0:01:10.380,0:01:16.140 I am so many years and am I too old to become a programmer? 0:01:16.140,0:01:21.120 And those questions are coming from people who are 50, who are 60, but also people who are 15. 0:01:21.660,0:01:25.260 So what is going on? We try to understand 0:01:25.260,0:01:32.940 together with Sebastian Valdes and George Park, how exactly this public discourse surrounding 0:01:32.940,0:01:39.660 age and software developers is organized? What are people talking about and what 0:01:39.660,0:01:43.800 kind of things they associate with being old in software development? 0:01:45.060,0:01:54.660 So we have analyzed articles, so essentially we have looked at the top 100 hits, 0:01:55.560,0:02:00.180 we looked at Google "age and software developer", we focused on English-based sources 0:02:00.180,0:02:03.780 and US-based locations, because of course age-related 0:02:03.780,0:02:08.460 expectations are culturally determined. We excluded things which are merely 0:02:08.460,0:02:14.760 job ads and collections of statistics and we found 24 articles published on news sites, 0:02:14.760,0:02:18.960 published on popular blog platform, CDC, a couple of those examples, 0:02:18.960,0:02:25.500 and we have manually analyzed those texts. So the first question for us was, 0:02:25.500,0:02:31.740 how old is actually old? And here I have bad news for many of us, 0:02:31.740,0:02:34.320 including myself. So I'm old: 0:02:34.320,0:02:39.180 I have passed the boundary of 40, so I am considered to be old. 0:02:40.200,0:02:46.260 And if you see that - even if the upper boundary from this table, like 50 or older, 0:02:46.260,0:02:53.100 is by far nowhere near to the retirement age in the western cultures. 0:02:54.600,0:02:59.580 Some documents even refer to people in their 30s as being old. 0:02:59.580,0:03:04.560 So essentially old is very young in software development. 0:03:05.760,0:03:11.520 So when we looked closer at what those articles are essentially talking about 0:03:11.520,0:03:15.900 then it turned out that employability is a major concern. 0:03:17.340,0:03:22.620 People are worried about their ability to continue their professional careers, 0:03:22.620,0:03:24.480 to find new jobs, and so on. 0:03:24.480,0:03:31.080 And we have cross-checked those articles with more popular opinions on Hacker News. 0:03:31.800,0:03:37.800 So what we have found is that there are many strategies which are being recommended 0:03:37.800,0:03:44.070 both for companies and for individuals when it comes to ensuring their employer - 0:03:44.070,0:03:48.180 employability of older software developers. For example, 0:03:48.180,0:03:56.700 companies can offer returnships which are often being mentioned in context of parental leaves, 0:03:56.700,0:04:02.160 but essentially can be used for any kind of extended career breaks. 0:04:02.760,0:04:09.480 Or provide career tracks and KPIs which would be tailored towards experienced developers. 0:04:09.480,0:04:16.380 At the same time companies should stop doing certain things which are negatively affecting 0:04:17.220,0:04:19.200 all the developers. For example, 0:04:19.200,0:04:27.000 if you are asking at the in - as part of your interview process to solve 0:04:27.000,0:04:32.040 classical puzzles from the algorithms book or from the data structures book from a 0:04:32.040,0:04:36.000 first-year university education then of course you are going to 0:04:36.960,0:04:41.640 disadvantage people who might not have followed the traditional path 0:04:41.640,0:04:47.520 or might not might have just followed those traditional paths many, many years ago, 0:04:47.520,0:04:50.520 which was of course the case for people we've been focusing on. 0:04:52.020,0:05:01.080 Framing technological experience as technology baggage is discouraging and worrisome. 0:05:01.620,0:05:07.260 At the level of the individuals, we see that these people are 0:05:07.260,0:05:11.760 trying to grow as software engineers, for example by mastering modern technologies 0:05:11.760,0:05:19.140 or developing mentorship skills or becoming - and getting knowledge of specific niche technologies, 0:05:20.100,0:05:25.260 but those techniques can be seen as problematic because even if your technology 0:05:25.260,0:05:31.140 knowledge is being appreciated, it's - the social context might be a problem 0:05:31.140,0:05:38.160 pushing some of the older individuals to adopt strategies which are aiming at appearing young. 0:05:38.160,0:05:43.260 For example modifying CV by hiding some of the previous employment, 0:05:44.580,0:05:50.400 working overtime which is mostly associated - not adopted for people having other obligations, 0:05:50.400,0:05:55.440 or even going to plastic surgeons. So based on the study, 0:05:55.440,0:06:03.960 we have seen techniques that both companies and individuals can employ to encourage or discourage 0:06:03.960,0:06:09.060 all the software developers from continuous - from being employed in companies. 0:06:10.020,0:06:15.300 In a follow-up study we have looked at more specific subgroup of all the developers, 0:06:15.300,0:06:19.500 specifically at women. Remember Masako Wakamiya? 0:06:19.500,0:06:24.780 She was in her 80s, she was developing an app. 0:06:24.780,0:06:30.540 We know from the literature and from our own experience that women are a minoritized 0:06:30.540,0:06:34.380 group in software development, and as our previous study has shown, 0:06:34.380,0:06:37.440 so are older developers. And in general 0:06:38.880,0:06:41.880 people who are on the intersection of multiple diversity axes 0:06:41.880,0:06:46.440 tend to experience challenges which cannot be attributed to a single one of them. 0:06:47.460,0:06:50.820 So this is why we have conducted a series of interview studies. 0:06:50.820,0:06:56.340 So you see here a general overview of the experiences of older women, 0:06:56.340,0:07:02.220 and again older in this case means 40 plus, the strategies they use to survive, 0:07:02.220,0:07:07.740 and their general perceptions. So this is of course a full-blown paper and 0:07:07.740,0:07:12.660 today I would like to focus solely on strategies because I would like to be it as practical 0:07:12.660,0:07:14.880 as possible. And specifically, 0:07:14.880,0:07:19.260 when we see the strategies that help women to survive in this hostile 0:07:19.260,0:07:25.440 or at least unfriendly environment we see age-related strategies such as 0:07:26.280,0:07:31.140 adjusting behavior or adjusting looks, we have already seen some of those issues before. 0:07:32.940,0:07:39.120 Studies which are related to gender, ranging from don't taking things personally 0:07:39.120,0:07:42.900 or baking other women, those strategies which 0:07:42.900,0:07:47.580 are trying to combine age - gender, because again we know that strategies 0:07:47.580,0:07:51.000 are not always easily attributed to a single of those dimensions. 0:07:51.000,0:07:57.780 And here you see two recommendations we have distilled from our interviews. 0:07:57.780,0:07:59.760 For example, trying to help the 0:07:59.760,0:08:08.460 next generation of women and non-binary people and of course also benefiting from the networks. 0:08:09.420,0:08:12.660 So summarizing, what have we seen? 0:08:12.660,0:08:22.260 We have seen that both organizations and individuals should and can invest 0:08:22.260,0:08:27.480 in creating more welcoming environment for all the developers in general and for 0:08:28.140,0:08:32.280 veteran women developers in particular. Of course, 0:08:32.280,0:08:40.980 it is a matter of common knowledge by now that diversity can bring more creative solutions and 0:08:40.980,0:08:46.320 can create more productive teams but specifically when we are 0:08:46.320,0:08:51.240 talking about minoritized groups - specifically when we are talking about 0:08:51.240,0:08:59.340 groups which are so scarce as older women and non-binary people in software development - 0:08:59.340,0:09:05.820 their inclusion allows us to approach the needs of 0:09:05.820,0:09:10.020 the underpresented - underserved groups in the society as a whole. 0:09:11.760,0:09:16.320 Examples of this kind of adjustments are of course changes in the interview process, 0:09:17.040,0:09:22.860 offering returnships, including KPIs or including 0:09:23.580,0:09:28.920 statements which would be refer - reflect that contributions of those people are valued 0:09:28.920,0:09:33.240 and are important for the company. When it comes to individual developers, 0:09:33.240,0:09:38.040 then of course we have quite a number of challenges there, 0:09:38.040,0:09:43.620 because we see people changing - challenging the environment or changing their environments. 0:09:45.120,0:09:49.800 Either, for example, through things like unionization, standing up against biases, 0:09:49.800,0:09:54.780 or simply by changing companies, roles, or sometimes locations. 0:09:55.920,0:09:59.880 We also see many much more problematic techniques and strategies, 0:09:59.880,0:10:03.180 such as adopting useful patterns of behavior, 0:10:04.140,0:10:09.840 changing looks, changing - sorry, 0:10:14.580,0:10:15.120 okay, 0:10:15.120,0:10:21.780 changing how people behave and how people look, but of course at the same time, 0:10:22.740,0:10:35.580 we know that those are merely band-aid solutions, while of course the problems are sometimes - or at 0:10:35.580,0:10:38.820 least most of them are systemic. And I apologize, 0:10:38.820,0:10:42.780 something happened to my screen and i'm not sure what exactly you are seeing. 0:10:48.540,0:10:51.600 We are seeing you at the moment the screen share has ended. 0:10:51.600,0:10:56.880 We've got - we've got time if you've got another slide or two and would like to try to reshare your 0:10:56.880,0:10:58.860 screen that should work. Okay, 0:10:58.860,0:11:05.640 let me just try to share it. Sure, 0:11:11.460,0:11:19.200 yep, we're seeing your screen but not your slides. Okay, so now you need to see the slides. 0:11:19.200,0:11:20.760 Yeah I know we're seeing the slides. Thank you. 0:11:20.760,0:11:22.920 So that's essentially this time, yes, 0:11:25.440,0:11:30.060 so as I said, right, so we have strategies and solutions which can help people 0:11:30.900,0:11:37.560 and you can help both companies and both companies and individuals 0:11:38.160,0:11:43.260 should be engaged in this process. And now I can actually stop sharing. 0:11:43.800,0:11:47.460 Okay, thank you very much, sorry for the technical hiccup there. 0:11:48.420,0:11:52.500 Great talk - thank you Alexander. A question coming in from the audience. 0:11:52.500,0:11:57.900 How is all of this going to play out with the demographic shift we're seeing, for example, 0:11:57.900,0:12:01.200 in Japan and parts of Europe, as we have an aging population. 0:12:02.520,0:12:05.700 Do you think that this sort of discrimination is going to be reduced? 0:12:08.100,0:12:14.400 I would love to say yes, but I don't really see it happening. 0:12:15.600,0:12:26.280 Our study has of course focused on the US-based labor market which is more hot, more active, 0:12:26.280,0:12:28.680 than what at least I see here in Europe, 0:12:29.940,0:12:34.140 and I probably should not make any comments about the Japanese labor market. 0:12:36.540,0:12:45.840 I'm mostly worried that, like, the problems we see are mostly related to changing employment. 0:12:47.160,0:12:51.120 If people are sticking around to the same companies, 0:12:51.120,0:12:53.820 they might be suffering but they will still around, 0:12:53.820,0:12:58.800 so they are not going to see it. The problems which came up were 0:12:58.800,0:13:04.560 mostly related to finding companies, being hired by those companies, and so on. 0:13:04.560,0:13:09.360 If the market is not that active, people are not likely to change their employment, 0:13:09.360,0:13:14.400 so we might have other forms of discrimination rather than the one we have seen. 0:13:14.400,0:13:21.360 But it will be very bold for me to claim that we are not going to have any forms of discrimination. 0:13:22.560,0:13:25.740 Okay, another another 0:13:25.740,0:13:30.060 comment that came up - or question - you mentioned changing appearance 0:13:30.900,0:13:34.020 How common is that in the tech sector, and how often are you 0:13:34.020,0:13:39.600 seeing people taking advantage of remote work to try to play down or even conceal their age? 0:13:41.400,0:13:47.880 So as a scientist I should say that those studies were qualitative, 0:13:47.880,0:13:51.060 so I cannot answer questions on the quantitative side, 0:13:51.060,0:13:53.040 I don't know how often it happens, 0:13:53.040,0:13:57.780 but it has been repeatedly mentioned at the very least. 0:13:57.780,0:14:03.540 So our interviewees are repeatedly mentioning changing their appearance, 0:14:03.540,0:14:09.420 either to appear younger or on the other side to not appear younger. 0:14:09.420,0:14:13.740 So most of the time when we are talking about changing appearance 0:14:13.740,0:14:18.600 we are thinking about trying to appear younger. Some people are not trying to appear younger, 0:14:18.600,0:14:23.640 in particular this was one of the topics which was related to our interviews with women. 0:14:25.920,0:14:29.940 I can maybe quote one of the interviewees, 0:14:29.940,0:14:36.240 she said that all those young tech bros, they don't like to work with their mom 0:14:36.240,0:14:40.620 but they are perfectly happy working with their grandmother. 0:14:43.560,0:14:50.160 So, this age, you know, it has a very strange relationship 0:14:50.160,0:14:59.260 with what makes you "of the right age". Women are often seen as never being right - 0:15:00.060,0:15:05.201 either to young and not taken seriously because they're too young 0:15:05.201,0:15:07.980 or they're too old and not taken seriously because their knowledge is our date, 0:15:07.980,0:15:10.260 right, so this - it's a tightrope.