The Haskell motto is "avoid success at all costs", usually clarified to "avoid 'success at all costs'".
In other words, "success" (popularity, widespread use in industry, teaching, etc.) is not a justification for "costs" such as limiting expressiveness, making things less safe, restricting research possibilities, etc. Haskell would prefer to be powerful, safe, efficient, obscure and niche; rather than popular, industry-standard, widely-known, highly compatible, unsafe, insecure, inefficient and restricted (besides, we have loads of languages of this sort!).
Crippling the language to make things easier for new users is not an option. However, there are many ways the language could be made easier without impacting any core values. For example, there are long-standing issues with strings, records, error messages, dependency handling, etc. which people are working on.
Also, for those who do want to learn Haskell, I've found the community to be very welcoming and tolerant of newbies. Just ignore some of the more math-heavy blog posts (for now, at least), or your head might explode :P
It's well known in the telecom/internet infrastructure business that Huawei:
a) bugged the hell out of Nortel's ottawa area offices, both physically, by rootkit, and by getting their own people hired to physically smuggle out documents and design data
b) Copied the entire DWDM / optical transport product line
c) Released a nearly identical product a few years later, and sold it at a ridiculously low price, effectively killing Nortel.
Many years later the vacant ex-Nortel office buildings came up for lease. One of the candidate tenants for that large of an office space were parts of the Canadian federal government, ministry of defence, etc. Every serious tenant passed on the space because it's so riddled with bugs.
When I got my PhD (1999) the American Physical Society said that you had a 2% chance of getting a permanent job in the field with a PhD. At that point you are not being judged on your merits but on your connections, ability to navigate politics, etc. (The job is way too valuable compared to the value you can give to it.)
I saw a postdoc who is now rather well known struggling with anxiety over his career even though he had written half a book and done a lot of great work. When we were both at Cornell I'd come to the conclusion that many papers involving "power law" distributions were bogus because nobody knew how to test for them with any rigor. It was years later, after he had tenure, that he published something about it in a statistics journal.
Seeing that made me run for the exit after my first year as a postdoc.
